rm(list=ls())
gc()
setwd("/hpc/group/pbenfeylab/CheWei/CW_data/genesys/")
| used | (Mb) | gc trigger | (Mb) | max used | (Mb) | |
|---|---|---|---|---|---|---|
| Ncells | 625379 | 33.4 | 1361498 | 72.8 | 1142547 | 61.1 |
| Vcells | 1159326 | 8.9 | 8388608 | 64.0 | 1802279 | 13.8 |
## Need seu4
suppressMessages(library(Seurat))
suppressMessages(library(cowplot))
suppressMessages(library(scattermore))
suppressMessages(library(scater))
suppressMessages(library(cowplot))
suppressMessages(library(RColorBrewer))
suppressMessages(library(grid))
suppressMessages(library(gplots))
suppressMessages(library(circular))
suppressMessages(library(ggplot2))
suppressMessages(library(ggnewscale))
suppressMessages(library(tidyverse))
suppressMessages(library(ComplexHeatmap))
suppressMessages(library(circlize))
suppressMessages(library(patchwork))
sessionInfo()
R version 4.2.2 (2022-10-31) Platform: x86_64-conda-linux-gnu (64-bit) Running under: CentOS Stream 8 Matrix products: default BLAS/LAPACK: /hpc/group/pbenfeylab/ch416/miniconda3/envs/seu4/lib/libopenblasp-r0.3.21.so locale: [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] grid stats4 stats graphics grDevices utils datasets [8] methods base other attached packages: [1] patchwork_1.1.3 circlize_0.4.15 [3] ComplexHeatmap_2.14.0 forcats_0.5.2 [5] stringr_1.5.1 dplyr_1.1.3 [7] purrr_1.0.2 readr_2.1.3 [9] tidyr_1.3.0 tibble_3.2.1 [11] tidyverse_1.3.2 ggnewscale_0.4.8 [13] circular_0.4-95 gplots_3.1.3 [15] RColorBrewer_1.1-3 scater_1.26.0 [17] ggplot2_3.4.4 scuttle_1.8.0 [19] SingleCellExperiment_1.20.0 SummarizedExperiment_1.28.0 [21] Biobase_2.58.0 GenomicRanges_1.50.0 [23] GenomeInfoDb_1.34.8 IRanges_2.32.0 [25] S4Vectors_0.36.0 BiocGenerics_0.44.0 [27] MatrixGenerics_1.10.0 matrixStats_1.1.0 [29] scattermore_1.2 cowplot_1.1.1 [31] SeuratObject_5.0.0 Seurat_4.1.1.9001 loaded via a namespace (and not attached): [1] utf8_1.2.4 spatstat.explore_3.2-5 [3] reticulate_1.34.0 tidyselect_1.2.0 [5] htmlwidgets_1.6.2 BiocParallel_1.32.5 [7] Rtsne_0.16 munsell_0.5.0 [9] ScaledMatrix_1.6.0 codetools_0.2-19 [11] ica_1.0-3 pbdZMQ_0.3-8 [13] future_1.33.0 miniUI_0.1.1.1 [15] withr_2.5.2 spatstat.random_3.2-1 [17] colorspace_2.1-0 progressr_0.14.0 [19] uuid_1.1-0 ROCR_1.0-11 [21] tensor_1.5 listenv_0.9.0 [23] repr_1.1.4 GenomeInfoDbData_1.2.9 [25] polyclip_1.10-6 parallelly_1.36.0 [27] vctrs_0.6.4 generics_0.1.3 [29] timechange_0.1.1 doParallel_1.0.17 [31] R6_2.5.1 clue_0.3-64 [33] ggbeeswarm_0.7.1 rsvd_1.0.5 [35] bitops_1.0-7 spatstat.utils_3.0-4 [37] DelayedArray_0.24.0 assertthat_0.2.1 [39] promises_1.2.1 scales_1.2.1 [41] googlesheets4_1.0.1 beeswarm_0.4.0 [43] gtable_0.3.4 beachmat_2.14.0 [45] globals_0.16.2 goftest_1.2-3 [47] spam_2.10-0 rlang_1.1.2 [49] GlobalOptions_0.1.2 splines_4.2.2 [51] lazyeval_0.2.2 gargle_1.2.1 [53] spatstat.geom_3.2-7 broom_1.0.2 [55] modelr_0.1.10 reshape2_1.4.4 [57] abind_1.4-5 backports_1.4.1 [59] httpuv_1.6.12 tools_4.2.2 [61] ellipsis_0.3.2 ggridges_0.5.4 [63] Rcpp_1.0.11 plyr_1.8.9 [65] base64enc_0.1-3 sparseMatrixStats_1.10.0 [67] zlibbioc_1.44.0 RCurl_1.98-1.6 [69] deldir_1.0-9 GetoptLong_1.0.5 [71] pbapply_1.7-2 viridis_0.6.4 [73] zoo_1.8-12 haven_2.5.1 [75] ggrepel_0.9.4 cluster_2.1.4 [77] fs_1.6.3 magrittr_2.0.3 [79] data.table_1.14.8 RSpectra_0.16-1 [81] reprex_2.0.2 lmtest_0.9-40 [83] RANN_2.6.1 googledrive_2.0.0 [85] mvtnorm_1.1-3 fitdistrplus_1.1-11 [87] hms_1.1.2 mime_0.12 [89] evaluate_0.23 xtable_1.8-4 [91] readxl_1.4.1 shape_1.4.6 [93] fastDummies_1.7.3 gridExtra_2.3 [95] compiler_4.2.2 KernSmooth_2.23-20 [97] crayon_1.5.2 htmltools_0.5.7 [99] tzdb_0.3.0 later_1.3.1 [101] lubridate_1.9.0 DBI_1.1.3 [103] dbplyr_2.2.1 MASS_7.3-58.3 [105] boot_1.3-28.1 Matrix_1.6-3 [107] cli_3.6.1 parallel_4.2.2 [109] dotCall64_1.1-0 igraph_1.5.1 [111] pkgconfig_2.0.3 sp_2.1-1 [113] IRdisplay_1.1 plotly_4.10.3 [115] spatstat.sparse_3.0-3 foreach_1.5.2 [117] xml2_1.3.3 vipor_0.4.5 [119] XVector_0.38.0 rvest_1.0.3 [121] digest_0.6.33 sctransform_0.4.1 [123] RcppAnnoy_0.0.21 spatstat.data_3.0-3 [125] cellranger_1.1.0 leiden_0.4.3 [127] uwot_0.1.16 DelayedMatrixStats_1.20.0 [129] shiny_1.7.5.1 gtools_3.9.4 [131] rjson_0.2.21 lifecycle_1.0.4 [133] nlme_3.1-162 jsonlite_1.8.7 [135] BiocNeighbors_1.16.0 viridisLite_0.4.2 [137] fansi_1.0.5 pillar_1.9.0 [139] lattice_0.21-8 fastmap_1.1.1 [141] httr_1.4.7 survival_3.4-0 [143] glue_1.6.2 iterators_1.0.14 [145] png_0.1-8 stringi_1.8.1 [147] RcppHNSW_0.5.0 BiocSingular_1.14.0 [149] caTools_1.18.2 IRkernel_1.3.1.9000 [151] irlba_2.3.5.1 future.apply_1.11.0
wanted_TFs <- read.csv("./Kay_TF_thalemine_annotations.csv")
nrow(wanted_TFs)
## Make TF names unique
wanted_TFs$Name[wanted_TFs$GeneID=="AT2G33880"]="WOX9"
wanted_TFs$Name[wanted_TFs$GeneID=="AT2G45160"]="SCL27"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G04410"]="NAC78"
wanted_TFs$Name[wanted_TFs$GeneID=="AT3G29035"]="ORS1"
wanted_TFs$Name[wanted_TFs$GeneID=="AT2G02540"]="ZHD3"
wanted_TFs$Name[wanted_TFs$GeneID=="AT3G16500"]="IAA26"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G09740"]="HAG5"
wanted_TFs$Name[wanted_TFs$GeneID=="AT4G24660"]="ZHD2"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G46880"]="HDG5"
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G28420"]="RLT1"
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G14580"]="BLJ"
wanted_TFs$Name[wanted_TFs$GeneID=="AT3G45260"]="BIB"
wanted_TFs$Name[wanted_TFs$GeneID=="AT2G02070"]="RVN"
wanted_TFs$Name[wanted_TFs$GeneID=="AT2G28160"]="FIT"
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G68360"]="GIS3"
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G20640"]="NLP4"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G05550"]="VFP5"
wanted_TFs$Name[wanted_TFs$GeneID=="AT3G59470"]="FRF1"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G15150"]="HAT7"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G14750"]="WER"
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G75710"]="BRON"
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G74500"]="TMO7"
wanted_TFs$Name[wanted_TFs$GeneID=="AT2G12646"]="RITF1"
wanted_TFs$Name[wanted_TFs$GeneID=="AT3G48100"]="ARR5"
wanted_TFs$Name[wanted_TFs$GeneID=="AT4G16141"]="GATA17L"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G65640"]="NFL"
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G62700"]="VND5"
wanted_TFs$Name[wanted_TFs$GeneID=="AT4G36160"]="VND2"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G66300"]="VND3"
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G12260"]="VND4"
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G62380"]="VND6"
## TTG1
wanted_TFs$Name[wanted_TFs$GeneID=="AT5G24520"]
## SCRAMBLED
wanted_TFs$Name[wanted_TFs$GeneID=="AT1G11130"]
## CAPRICE
wanted_TFs$Name[wanted_TFs$GeneID=="AT2G46410"]
stem2pro <- read.csv("./TF_GRN_centrality_t0-t1_zscore3.csv")
pro2trans <- read.csv("./TF_GRN_centrality_t1-t3_zscore3.csv")
trans2el <- read.csv("./TF_GRN_centrality_t3-t5_zscore3.csv")
el2el <- read.csv("./TF_GRN_centrality_t5-t7_zscore3.csv")
el2mat <- read.csv("./TF_GRN_centrality_t7-t9_zscore3.csv")
head(stem2pro)
| X | tf_occurance | atri_degree_centrality | atri_out_centrality | atri_in_centrality | atri_betweenness_centrality | atri_closeness_centrality | atri_eigenvector_centrality | tri_degree_centrality | tri_out_centrality | ... | phl_in_centrality | phl_betweenness_centrality | phl_closeness_centrality | phl_eigenvector_centrality | col_degree_centrality | col_out_centrality | col_in_centrality | col_betweenness_centrality | col_closeness_centrality | col_eigenvector_centrality | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | ... | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| 1 | GAMMA-H2AX | 10 | 1.0481586 | 0.35127479 | 0.69688385 | 0.8173690 | 0.002480878 | 0.12299414 | 0.74551971 | 0.12903226 | ... | 0.09969168 | 0.6445045 | 0.0003312703 | 0.05985332 | 0.2263711 | 0.18553092 | 0.04084014 | 0.0001635787 | 0.0005359491 | 0.06437981 |
| 2 | HB-2 | 9 | 0.2521246 | 0.15580737 | 0.09631728 | 0.3296259 | 0.001392521 | 0.05177987 | 0.05017921 | 0.01792115 | ... | 0.20760534 | 0.9541161 | 0.0004221278 | 0.08107215 | 0.4037340 | 0.15985998 | 0.24387398 | 0.8044362534 | 0.0006764851 | 0.08090327 |
| 3 | CRF2 | 9 | 0.7535411 | 0.45892351 | 0.29461756 | 0.7579030 | 0.002018580 | 0.10303448 | 1.05376344 | 0.61648746 | ... | 0.14799589 | 0.9041508 | 0.0003743185 | 0.06718402 | 1.2240373 | 0.84014002 | 0.38389732 | 0.9883559254 | 0.0007417819 | 0.12383249 |
| 4 | HDA3 | 8 | 0.8583569 | 0.05665722 | 0.80169972 | 0.9935778 | 0.002648215 | 0.11849391 | 1.27956989 | 0.44802867 | ... | 0.00000000 | 0.0000000 | 0.0000000000 | 0.00000000 | 0.3080513 | 0.23103851 | 0.07701284 | 0.1441496090 | 0.0006045867 | 0.06877130 |
| 5 | HMGB6 | 8 | 0.3201133 | 0.27762040 | 0.04249292 | 0.0000000 | 0.002007357 | 0.07062791 | 0.39068100 | 0.26164875 | ... | 0.06166495 | 0.8344763 | 0.0003372956 | 0.04870876 | 0.1155193 | 0.09801634 | 0.01750292 | 0.0000000000 | 0.0006302146 | 0.04251342 |
| 6 | HAT1 | 8 | 0.3767705 | 0.15297450 | 0.22379603 | 0.2972653 | 0.001926347 | 0.07873702 | 0.13261649 | 0.11827957 | ... | 0.28365879 | 0.9619246 | 0.0004216832 | 0.08605297 | 0.4714119 | 0.35355893 | 0.11785298 | 0.7370009488 | 0.0007078086 | 0.08331075 |
head(pro2trans)
| X | tf_occurance | atri_degree_centrality | atri_out_centrality | atri_in_centrality | atri_betweenness_centrality | atri_closeness_centrality | atri_eigenvector_centrality | tri_degree_centrality | tri_out_centrality | ... | phl_in_centrality | phl_betweenness_centrality | phl_closeness_centrality | phl_eigenvector_centrality | col_degree_centrality | col_out_centrality | col_in_centrality | col_betweenness_centrality | col_closeness_centrality | col_eigenvector_centrality | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | ... | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| 1 | HAT1 | 8 | 0.4607843 | 0.27647059 | 0.18431373 | 3.133403e-02 | 0.001327612 | 0.08696905 | 0.04144385 | 0.00802139 | ... | 0.038500507 | 0.203569322 | 0.0003311874 | 0.022256053 | 0.15838150 | 0.06820809 | 0.09017341 | 0.000000000 | 0.0002910342 | 0.04766973 |
| 2 | GAMMA-H2AX | 8 | 0.7196078 | 0.29215686 | 0.42745098 | 9.884241e-01 | 0.001408803 | 0.09728463 | 0.21657754 | 0.09358289 | ... | 0.016210740 | 0.000000000 | 0.0002320833 | 0.020539257 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.0000000000 | 0.00000000 |
| 3 | GRP2B | 8 | 0.2745098 | 0.14901961 | 0.12549020 | 3.852229e-05 | 0.001301947 | 0.06493313 | 0.07486631 | 0.06283422 | ... | 0.332320162 | 0.003706398 | 0.0003966881 | 0.080845333 | 0.27514451 | 0.18381503 | 0.09132948 | 0.044570221 | 0.0003646495 | 0.06817366 |
| 4 | BME3 | 7 | 0.1372549 | 0.07647059 | 0.06078431 | 1.896105e-01 | 0.001088849 | 0.03910060 | 0.11363636 | 0.07352941 | ... | 0.032421479 | 0.037009521 | 0.0002207693 | 0.018088461 | 0.04855491 | 0.02658960 | 0.02196532 | 0.003753211 | 0.0002726701 | 0.02049709 |
| 5 | GATA2 | 7 | 1.2980392 | 0.56862745 | 0.72941176 | 9.796833e-01 | 0.001664178 | 0.12572860 | 1.54946524 | 0.95989305 | ... | 0.001013171 | 0.003943764 | 0.0001739663 | 0.003335369 | 0.09942197 | 0.04508671 | 0.05433526 | 0.078709056 | 0.0003095810 | 0.03070615 |
| 6 | HB20 | 7 | 0.4019608 | 0.01764706 | 0.38431373 | 1.637929e-01 | 0.001266621 | 0.08316733 | 0.05614973 | 0.00802139 | ... | 0.098277609 | 0.070318810 | 0.0003035202 | 0.044232294 | 0.20115607 | 0.18843931 | 0.01271676 | 0.001540088 | 0.0003809927 | 0.05735016 |
head(trans2el)
| X | tf_occurance | atri_degree_centrality | atri_out_centrality | atri_in_centrality | atri_betweenness_centrality | atri_closeness_centrality | atri_eigenvector_centrality | tri_degree_centrality | tri_out_centrality | ... | phl_in_centrality | phl_betweenness_centrality | phl_closeness_centrality | phl_eigenvector_centrality | col_degree_centrality | col_out_centrality | col_in_centrality | col_betweenness_centrality | col_closeness_centrality | col_eigenvector_centrality | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | ... | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| 1 | HB20 | 8 | 0.29893238 | 0.12099644 | 0.177935943 | 0.7943333270 | 0.0005577957 | 0.10535727 | 0.231040564 | 0.194003527 | ... | 0.06226650 | 0.16547672 | 0.0003305909 | 0.041245684 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000e+00 | 0.0000000000 | 0.00000000 |
| 2 | AT4G30410 | 8 | 0.70106762 | 0.10142349 | 0.599644128 | 0.5661090706 | 0.0005652264 | 0.16819541 | 1.223985891 | 0.895943563 | ... | 0.02739726 | 0.02991742 | 0.0003475172 | 0.036212288 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000e+00 | 0.0000000000 | 0.00000000 |
| 3 | UPB1 | 7 | 0.85587189 | 0.03736655 | 0.818505338 | 0.3010669813 | 0.0006138503 | 0.18742391 | 0.089947090 | 0.037037037 | ... | 0.04732254 | 0.00000000 | 0.0003551783 | 0.044442949 | 0.05555556 | 0.04678363 | 0.00877193 | 0.000000e+00 | 0.0005728614 | 0.02830553 |
| 4 | BZIP61 | 7 | 0.14234875 | 0.07829181 | 0.064056940 | 0.5917622953 | 0.0004299594 | 0.06355916 | 0.068783069 | 0.061728395 | ... | 0.09589041 | 0.67429030 | 0.0004204217 | 0.062160969 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000e+00 | 0.0000000000 | 0.00000000 |
| 5 | HAT1 | 6 | 0.01779359 | 0.01601423 | 0.001779359 | 0.0000000000 | 0.0003900365 | 0.01711689 | 0.008818342 | 0.007054674 | ... | 0.01867995 | 0.47303907 | 0.0004062287 | 0.051264227 | 0.07163743 | 0.06286550 | 0.00877193 | 0.000000e+00 | 0.0005106317 | 0.03622616 |
| 6 | AT1G74840 | 6 | 0.16725979 | 0.10142349 | 0.065836299 | 0.0008532044 | 0.0005357602 | 0.07918305 | 0.052910053 | 0.042328042 | ... | 0.00124533 | 0.00000000 | 0.0002016686 | 0.003987783 | 0.10672515 | 0.08479532 | 0.02192982 | 3.638917e-05 | 0.0008461764 | 0.04511538 |
head(el2el)
| X | tf_occurance | atri_degree_centrality | atri_out_centrality | atri_in_centrality | atri_betweenness_centrality | atri_closeness_centrality | atri_eigenvector_centrality | tri_degree_centrality | tri_out_centrality | ... | phl_in_centrality | phl_betweenness_centrality | phl_closeness_centrality | phl_eigenvector_centrality | col_degree_centrality | col_out_centrality | col_in_centrality | col_betweenness_centrality | col_closeness_centrality | col_eigenvector_centrality | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | ... | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| 1 | UPB1 | 9 | 0.4441558 | 0.21818182 | 0.22597403 | 0.426102543 | 0.0005882946 | 0.11339911 | 0.06851852 | 0.03703704 | ... | 0.043907794 | 1.172483e-02 | 0.0002748839 | 0.04073606 | 0.17448680 | 0.16129032 | 0.01319648 | 0.001937809 | 0.0007443138 | 0.06616948 |
| 2 | HAT22 | 9 | 0.2831169 | 0.06493506 | 0.21818182 | 0.358887987 | 0.0005878071 | 0.09088137 | 0.40370370 | 0.11851852 | ... | 0.016465423 | 5.186910e-05 | 0.0002271318 | 0.02549151 | 0.08651026 | 0.07038123 | 0.01612903 | 0.052760086 | 0.0007253234 | 0.03748769 |
| 3 | WLIM1 | 8 | 0.1246753 | 0.01038961 | 0.11428571 | 0.376048431 | 0.0004643862 | 0.05776708 | 0.11666667 | 0.03518519 | ... | 0.062568606 | 1.502756e-02 | 0.0003027703 | 0.05051630 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.0000000000 | 0.00000000 |
| 4 | AT4G30410 | 7 | 0.2000000 | 0.13246753 | 0.06753247 | 0.005756223 | 0.0005111366 | 0.07034153 | 0.78518519 | 0.65555556 | ... | 0.007683864 | 2.050639e-05 | 0.0002316630 | 0.02502566 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.0000000000 | 0.00000000 |
| 5 | LEP | 7 | 0.7636364 | 0.69610390 | 0.06753247 | 0.296340639 | 0.0006628421 | 0.15817165 | 0.82962963 | 0.75185185 | ... | 0.019758507 | 1.952811e-02 | 0.0002128259 | 0.02351468 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.0000000000 | 0.00000000 |
| 6 | GBF6 | 6 | 0.0000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.0000000000 | 0.00000000 | 0.00000000 | 0.00000000 | ... | 0.506037322 | 3.889941e-02 | 0.0003675904 | 0.13792428 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.0000000000 | 0.00000000 |
head(el2mat)
| X | tf_occurance | atri_degree_centrality | atri_out_centrality | atri_in_centrality | atri_betweenness_centrality | atri_closeness_centrality | atri_eigenvector_centrality | tri_degree_centrality | tri_out_centrality | ... | phl_in_centrality | phl_betweenness_centrality | phl_closeness_centrality | phl_eigenvector_centrality | col_degree_centrality | col_out_centrality | col_in_centrality | col_betweenness_centrality | col_closeness_centrality | col_eigenvector_centrality | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | ... | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| 1 | AXR3 | 8 | 0.7809798 | 0.1354467 | 0.64553314 | 0.9945362 | 0.0008515654 | 0.12600157 | 0.00000000 | 0.00000000 | ... | 0.004592423 | 1.807936e-04 | 0.0001297446 | 0.006055279 | 0.78768577 | 0.59023355 | 0.19745223 | 0.019943985 | 0.0014164778 | 0.11644417 |
| 2 | HB-7 | 6 | 0.1873199 | 0.1671470 | 0.02017291 | 0.0000000 | 0.0007831216 | 0.06742666 | 0.10954064 | 0.08833922 | ... | 0.011481056 | 2.630086e-03 | 0.0002391847 | 0.025527182 | 0.06794055 | 0.02547771 | 0.04246285 | 0.000000000 | 0.0006447161 | 0.02364832 |
| 3 | RAV1 | 6 | 0.4726225 | 0.1930836 | 0.27953890 | 0.6033216 | 0.0007660186 | 0.10581265 | 0.20494700 | 0.03886926 | ... | 0.026406429 | 1.187695e-05 | 0.0002787072 | 0.041845397 | 0.12101911 | 0.08492569 | 0.03609342 | 0.004223698 | 0.0007212557 | 0.04033330 |
| 4 | HAT22 | 6 | 0.9798271 | 0.7146974 | 0.26512968 | 0.5695391 | 0.0010049655 | 0.14327323 | 0.43462898 | 0.16254417 | ... | 0.009184845 | 0.000000e+00 | 0.0002073287 | 0.014163359 | 0.05732484 | 0.03397028 | 0.02335456 | 0.014008222 | 0.0005989863 | 0.02039925 |
| 5 | RD26 | 6 | 1.0288184 | 0.5734870 | 0.45533141 | 0.7858523 | 0.0008992893 | 0.14485878 | 0.48409894 | 0.24028269 | ... | 0.040183697 | 2.441374e-04 | 0.0002800148 | 0.044217242 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.0000000000 | 0.00000000 |
| 6 | MYB7 | 6 | 0.6195965 | 0.3688761 | 0.25072046 | 0.4572721 | 0.0008324031 | 0.12487370 | 0.08480565 | 0.02120141 | ... | 0.000000000 | 0.000000e+00 | 0.0000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.0000000000 | 0.00000000 |
head(trans2el)
| X | tf_occurance | atri_degree_centrality | atri_out_centrality | atri_in_centrality | atri_betweenness_centrality | atri_closeness_centrality | atri_eigenvector_centrality | tri_degree_centrality | tri_out_centrality | ... | phl_in_centrality | phl_betweenness_centrality | phl_closeness_centrality | phl_eigenvector_centrality | col_degree_centrality | col_out_centrality | col_in_centrality | col_betweenness_centrality | col_closeness_centrality | col_eigenvector_centrality | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | ... | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| 1 | HB20 | 8 | 0.29893238 | 0.12099644 | 0.177935943 | 0.7943333270 | 0.0005577957 | 0.10535727 | 0.231040564 | 0.194003527 | ... | 0.06226650 | 0.16547672 | 0.0003305909 | 0.041245684 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000e+00 | 0.0000000000 | 0.00000000 |
| 2 | AT4G30410 | 8 | 0.70106762 | 0.10142349 | 0.599644128 | 0.5661090706 | 0.0005652264 | 0.16819541 | 1.223985891 | 0.895943563 | ... | 0.02739726 | 0.02991742 | 0.0003475172 | 0.036212288 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000e+00 | 0.0000000000 | 0.00000000 |
| 3 | UPB1 | 7 | 0.85587189 | 0.03736655 | 0.818505338 | 0.3010669813 | 0.0006138503 | 0.18742391 | 0.089947090 | 0.037037037 | ... | 0.04732254 | 0.00000000 | 0.0003551783 | 0.044442949 | 0.05555556 | 0.04678363 | 0.00877193 | 0.000000e+00 | 0.0005728614 | 0.02830553 |
| 4 | BZIP61 | 7 | 0.14234875 | 0.07829181 | 0.064056940 | 0.5917622953 | 0.0004299594 | 0.06355916 | 0.068783069 | 0.061728395 | ... | 0.09589041 | 0.67429030 | 0.0004204217 | 0.062160969 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000e+00 | 0.0000000000 | 0.00000000 |
| 5 | HAT1 | 6 | 0.01779359 | 0.01601423 | 0.001779359 | 0.0000000000 | 0.0003900365 | 0.01711689 | 0.008818342 | 0.007054674 | ... | 0.01867995 | 0.47303907 | 0.0004062287 | 0.051264227 | 0.07163743 | 0.06286550 | 0.00877193 | 0.000000e+00 | 0.0005106317 | 0.03622616 |
| 6 | AT1G74840 | 6 | 0.16725979 | 0.10142349 | 0.065836299 | 0.0008532044 | 0.0005357602 | 0.07918305 | 0.052910053 | 0.042328042 | ... | 0.00124533 | 0.00000000 | 0.0002016686 | 0.003987783 | 0.10672515 | 0.08479532 | 0.02192982 | 3.638917e-05 | 0.0008461764 | 0.04511538 |
min_max_normalize <- function(data) {
min_val <- min(data)
max_val <- max(data)
normalized_data <- (data - min_val) / (max_val - min_val)
return(normalized_data)
}
summary(stem2pro$tri_betweenness_centrality)
Min. 1st Qu. Median Mean 3rd Qu. Max. 0.00000 0.00000 0.00000 0.02406 0.00000 0.98597
summary(min_max_normalize(stem2pro$tri_betweenness_centrality))
Min. 1st Qu. Median Mean 3rd Qu. Max. 0.0000 0.0000 0.0000 0.0244 0.0000 1.0000
ncol(stem2pro)
stem2pro <- as.data.frame(cbind(stem2pro[,1],apply(stem2pro[,3:62],2,min_max_normalize)))
pro2trans <- as.data.frame(cbind(pro2trans[,1],apply(pro2trans[,3:62],2,min_max_normalize)))
trans2el <- as.data.frame(cbind(trans2el[,1],apply(trans2el[,3:62],2,min_max_normalize)))
el2el <- as.data.frame(cbind(el2el[,1],apply(el2el[,3:62],2,min_max_normalize)))
el2mat <- as.data.frame(cbind(el2mat[,1],apply(el2mat[,3:62],2,min_max_normalize)))
dat <- stem2pro %>%
full_join(pro2trans, by = "V1") %>%
full_join(trans2el, by = "V1") %>%
full_join(el2el, by = "V1") %>%
full_join(el2mat, by = "V1")
dat[is.na(dat)] <- 0
n <- c('atri_degree_centrality','atri_out_centrality','atri_in_centrality','atri_betweenness_centrality','atri_closeness_centrality','atri_eigenvector_centrality',
'tri_degree_centrality','tri_out_centrality','tri_in_centrality','tri_betweenness_centrality','tri_closeness_centrality','tri_eigenvector_centrality',
'lrc_degree_centrality','lrc_out_centrality','lrc_in_centrality','lrc_betweenness_centrality','lrc_closeness_centrality','lrc_eigenvector_centrality',
'cor_degree_centrality','cor_out_centrality','cor_in_centrality','cor_betweenness_centrality','cor_closeness_centrality','cor_eigenvector_centrality',
'end_degree_centrality','end_out_centrality','end_in_centrality','end_betweenness_centrality','end_closeness_centrality','end_eigenvector_centrality',
'per_degree_centrality','per_out_centrality','per_in_centrality','per_betweenness_centrality','per_closeness_centrality','per_eigenvector_centrality',
'pro_degree_centrality','pro_out_centrality','pro_in_centrality','pro_betweenness_centrality','pro_closeness_centrality','pro_eigenvector_centrality',
'xyl_degree_centrality','xyl_out_centrality','xyl_in_centrality','xyl_betweenness_centrality','xyl_closeness_centrality','xyl_eigenvector_centrality',
'phl_degree_centrality','phl_out_centrality','phl_in_centrality','phl_betweenness_centrality','phl_closeness_centrality','phl_eigenvector_centrality',
'col_degree_centrality','col_out_centrality','col_in_centrality','col_betweenness_centrality','col_closeness_centrality','col_eigenvector_centrality')
colnames(dat) <- c("TF",gsub("$","_1",n), gsub("$","_2",n),gsub("$","_3",n),gsub("$","_4",n),gsub("$","_5",n))
GeneID <- wanted_TFs$GeneID[match(dat$TF, wanted_TFs$Name)]
dat <- cbind(GeneID, dat)
head(dat)
| GeneID | TF | atri_degree_centrality_1 | atri_out_centrality_1 | atri_in_centrality_1 | atri_betweenness_centrality_1 | atri_closeness_centrality_1 | atri_eigenvector_centrality_1 | tri_degree_centrality_1 | tri_out_centrality_1 | ... | phl_in_centrality_5 | phl_betweenness_centrality_5 | phl_closeness_centrality_5 | phl_eigenvector_centrality_5 | col_degree_centrality_5 | col_out_centrality_5 | col_in_centrality_5 | col_betweenness_centrality_5 | col_closeness_centrality_5 | col_eigenvector_centrality_5 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | ... | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | |
| 1 | AT1G54690 | GAMMA-H2AX | 0.719844357976654 | 0.382716049382716 | 0.869257950530035 | 0.822652238008068 | 0.927975058549276 | 0.922339387205014 | 0.533333333333333 | 0.143426294820717 | ... | 0.00458715596330275 | 0 | 0.461497006723908 | 0.0361027357633705 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2 | AT4G16780 | HB-2 | 0.173151750972763 | 0.169753086419753 | 0.120141342756184 | 0.331756548785822 | 0.520874058755548 | 0.388299883582212 | 0.0358974358974359 | 0.0199203187250996 | ... | 0.00114678899082569 | 0 | 0.459827872532017 | 0.0361027357633705 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3 | AT4G23750 | CRF2 | 0.517509727626459 | 0.5 | 0.367491166077739 | 0.762801924541139 | 0.755052116281518 | 0.772660846729075 | 0.753846153846154 | 0.685258964143426 | ... | 0.0160550458715596 | 0 | 0.646169693735806 | 0.152197951166501 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4 | AT3G44750 | HDA3 | 0.589494163424125 | 0.0617283950617284 | 1 | 1 | 0.990567579310647 | 0.88859191221792 | 0.915384615384615 | 0.49800796812749 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 5 | AT5G23420 | HMGB6 | 0.219844357976654 | 0.302469135802469 | 0.0530035335689046 | 0 | 0.75085417652198 | 0.529642376608434 | 0.279487179487179 | 0.290836653386454 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 6 | AT4G17460 | HAT1 | 0.25875486381323 | 0.166666666666667 | 0.279151943462898 | 0.299186767969674 | 0.720552196291768 | 0.590452970620055 | 0.0948717948717949 | 0.131474103585657 | ... | 0.00344036697247706 | 0 | 0.481357647786302 | 0.0361027357633705 | 0 | 0 | 0 | 0 | 0 | 0 |
numz <- function(x){
sum(x==0)/length(x)
}
dat$combined_score <- min_max_normalize(rowSums(apply(dat[,grep("centrality",colnames(dat))],2,as.numeric)))
dat$celltype_specificity <- min_max_normalize(apply(apply(dat[,grep("centrality",colnames(dat))],2,as.numeric),1,numz))
dat$weighted_score <- dat$combined_score + dat$celltype_specificity
dat <- dat %>% arrange(desc(weighted_score))
head(dat)
| GeneID | TF | atri_degree_centrality_1 | atri_out_centrality_1 | atri_in_centrality_1 | atri_betweenness_centrality_1 | atri_closeness_centrality_1 | atri_eigenvector_centrality_1 | tri_degree_centrality_1 | tri_out_centrality_1 | ... | phl_eigenvector_centrality_5 | col_degree_centrality_5 | col_out_centrality_5 | col_in_centrality_5 | col_betweenness_centrality_5 | col_closeness_centrality_5 | col_eigenvector_centrality_5 | combined_score | celltype_specificity | weighted_score | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | ... | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <chr> | <dbl> | <dbl> | <dbl> | |
| 1 | AT5G24800 | BZIP9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0.991510602104265 | 0 | 0 | 0 | 0 | 0 | 0 | 0.7446064 | 0.6120690 | 1.356675 |
| 2 | AT3G43430 | AT3G43430 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0.635753571515156 | 0 | 0 | 0 | 0 | 0 | 0 | 0.7633960 | 0.4698276 | 1.233224 |
| 3 | AT3G20840 | PLT1 | 0.447470817120623 | 0.216049382716049 | 0.565371024734982 | 0.963922953555055 | 0.802246769591505 | 0.771509226624259 | 0 | 0 | ... | 0 | 0.0614035087719298 | 0.0997566909975669 | 0.0022075055187638 | 0 | 0.590409461781574 | 0.239091323851849 | 0.5610944 | 0.6681034 | 1.229198 |
| 4 | AT5G15150 | HAT7 | 0 | 0 | 0 | 0 | 0 | 0 | 0.228205128205128 | 0.051792828685259 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.8650723 | 0.3534483 | 1.218521 |
| 5 | AT5G57620 | MYB36 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.5176350 | 0.6810345 | 1.198669 |
| 6 | AT2G45050 | GATA2 | 0.817120622568093 | 0.79320987654321 | 0.575971731448763 | 0.804800012959873 | 0.834697097968316 | 0.913662678649798 | 0.779487179487179 | 0.665338645418327 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.8562137 | 0.3146552 | 1.170869 |
write.csv(dat,"TF_GRN_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=FALSE)
gene_list <- read.table('./gene_list_1108.csv', sep=",", header = TRUE)
exptf <- intersect(gene_list$features, wanted_TFs$GeneID)
length(exptf)
sfun <- read.csv('string_functional_annotations.tsv', sep="\t", header=TRUE)
sann <- read.csv('string_protein_annotations.tsv', sep="\t", header=TRUE)
gsgo1 <- unique(sfun[grep('root|xylem|phloem|procambium|pericycle|vascular|vasculature|stele|tracheary|sieve|trichoblast|atrichoblast|epidermis|epidermal tissue|lateral root cap|root hair|trichome|cortex|endodermis|ground tissue|columella|quiescent center',sfun$term.description, ignore.case=TRUE),]$X.node)
gsgo2 <- unique(sann[grep('root|xylem|phloem|procambium|pericycle|vascular|vasculature|stele|tracheary|sieve|trichoblast|atrichoblast|epidermis|epidermal tissue|lateral root cap|root hair|trichome|cortex|endodermis|ground tissue|columella|quiescent center',sann$domain_summary_url, ignore.case=TRUE),]$X.node)
gsgo <- sort(unique(c(gsgo1, gsgo2)))
#write.csv(data.frame(GeneID=gsgo),"./Gold_Standard_Root_TF_StringDB.csv", quote=FALSE, row.names=FALSE)
length(gsgo)
gsgo
gsgo <- gsub(",.*$","",gsub("^.*ath:","",sann[match(gsgo, sann$X.node),]$other_names_and_aliases))
gsgo[which(gsgo=='831248')]='AT5G14000'
gsgo
sann[which(sann$X.node=="HAT7"),]
| X.node | identifier | domain_summary_url | annotation | other_names_and_aliases | |
|---|---|---|---|---|---|
| <chr> | <chr> | <chr> | <chr> | <chr> | |
| 668 | HAT7 | 3702.Q00466 | Homeobox-leucine zipper protein HAT7; Probable transcription factor. | https://smart.embl.de/smart/DDvec.cgi?smart=314:HOX(113|174)+ | 831367,AT5G15150,ATHB-3,At5g15150,F8M21_40,HAT7,HAT7_ARATH,HB-3,HD-ZIP protein 7,HD-ZIP protein ATHB-3,Homeobox 3,Homeobox-leucine zipper protein,Homeobox-leucine zipper protein HAT7,Homeodomain transcription factor ATHB-3,Homeodomain-leucine zipper protein HAT7,NM_121519.3,NP_568309,NP_568309.2,Q00466,Q0WNS2,Q9LXG6,ath:AT5G15150 |
sann[grep("831248",sann$other_names_and_aliases, ignore.case = TRUE),]
| X.node | identifier | domain_summary_url | annotation | other_names_and_aliases | |
|---|---|---|---|---|---|
| <chr> | <chr> | <chr> | <chr> | <chr> | |
| 980 | NAC084 | 3702.A0A1P8BAC2 | NAC domain containing protein 84. | https://smart.embl.de/smart/DDvec.cgi?smart=262:Pfam_NAM(16|196)+ | 831248,A0A1P8BAC2,A0A1P8BAC2_ARATH,At5g14000,MAC12.3,MAC12_3,NAC domain containing protein 84,NAC084,NM_001343305.1,NP_001330278.1,anac084 |
r50 <- 105
numz <- function(x){
sum(x==0)/length(x)
}
genesys <- dat
run_r50_genesys <- function(x){
genesys$combined_score <- min_max_normalize(rowSums(apply(genesys[,grep(x,colnames(genesys))],2,as.numeric)))
genesys <- genesys %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(genesys))){
if (genesys$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## all cell type : in centrality + celltype & dev stage specificity
#dat$combined_score <- min_max_normalize(rowSums(apply(dat[,grep("in_centrality",colnames(dat))],2,as.numeric)))
#dat$celltype_specificity <- min_max_normalize(apply(apply(dat[,grep("in_centrality",colnames(dat))],2,as.numeric),1,numz))
#dat$weighted_score <- dat$combined_score + dat$celltype_specificity
#dat <- dat %>% arrange(desc(weighted_score))
#count <- 0
#for (i in seq(nrow(dat))){
# if (dat$GeneID[i] %in% gsgo){
# count <- count +1
# if (count == r50){
# print(i)
# break
# }
# }
#}
prepros <- function(x){
dat <- read.csv(x)
#dat <- dat %>% filter(role=="Connector Hub")
dat <- dat[,c(1, grep("centrality",colnames(dat)), 22)]
return(dat)
}
atri <- prepros("../celloracle/atrichoblast_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
tri <- prepros("../celloracle/trichoblast_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
lrc <- prepros("../celloracle/lrc_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
cor <- prepros("../celloracle/cortex_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
end <- prepros("../celloracle/endodermis_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
per <- prepros("../celloracle/pericycle_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
pro <- prepros("../celloracle/procambium_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
xyl <- prepros("../celloracle/xylem_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
phl <- prepros("../celloracle/phloem_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
col <- prepros("../celloracle/columella_Root_Atlas_SCT_celloracle_gene_score_iGRN.csv")
dat <- rbind(atri, tri, lrc, cor, end, per, pro, xyl, phl, col)
## Remove those not present in the dataset
dat <- dat[!is.na(match(dat$X,exptf)),]
dat <- dat %>% group_by(cluster) %>% reframe(GeneID=X,degree_centrality = min_max_normalize(degree_centrality_all),
in_centrality = min_max_normalize(degree_centrality_in),
out_centrality = min_max_normalize(degree_centrality_out),
betweenness_centrality = min_max_normalize(betweenness_centrality),
closeness_centrality = min_max_normalize(closeness_centrality),
eigenvector_centrality = min_max_normalize(eigenvector_centrality))
dat <- dat %>% group_by(GeneID) %>% reframe(degree_centrality = sum(degree_centrality),
in_centrality = sum(in_centrality),
out_centrality = sum(out_centrality),
betweenness_centrality = sum(betweenness_centrality),
closeness_centrality = sum(closeness_centrality),
eigenvector_centrality = sum(eigenvector_centrality))
dat <- cbind(dat[,1],apply(dat[,2:7],2,min_max_normalize))
head(dat)
| GeneID | degree_centrality | in_centrality | out_centrality | betweenness_centrality | closeness_centrality | eigenvector_centrality | |
|---|---|---|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| 1 | AT1G01010 | 0.0849393998 | 0.065317964 | 0.081735954 | 2.592974e-02 | 0.3643692412 | 0.068339145 |
| 2 | AT1G01030 | 0.0009542021 | 0.000000000 | 0.004447568 | 0.000000e+00 | 0.0003449773 | 0.003632920 |
| 3 | AT1G01260 | 0.0233438132 | 0.000000000 | 0.033565069 | 0.000000e+00 | 0.0872081085 | 0.016136854 |
| 4 | AT1G01350 | 0.0293468347 | 0.134378356 | 0.000000000 | 0.000000e+00 | 0.0000000000 | 0.017764785 |
| 5 | AT1G01380 | 0.0035614661 | 0.005492245 | 0.004573149 | 7.240465e-05 | 0.0852853904 | 0.003752290 |
| 6 | AT1G01640 | 0.0060441842 | 0.023215800 | 0.000000000 | 0.000000e+00 | 0.0000000000 | 0.006672674 |
celloracle <- dat
run_r50_celloracle <- function(x){
celloracle$combined_score <- celloracle[,grep(x,colnames(celloracle))]
celloracle <- celloracle %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(celloracle))){
if (celloracle$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## all cell type : degree centrality + out centrality + in centrality + betweenness centrality + closeness + eigenvector
#dat$combined_score <- min_max_normalize(rowSums(apply(dat[,grep("centrality",colnames(dat))],2,as.numeric)))
#dat <- dat %>% arrange(desc(combined_score))
#count <- 0
#for (i in seq(nrow(dat))){
# if (dat$GeneID[i] %in% gsgo){
# count <- count +1
# if (count == r50){
# print(i)
# break
# }
# }
#}
#dat$combined_score <- min_max_normalize(rowSums(apply(dat[,grep("betweenness_centrality|celltype_specificity",colnames(dat))],2,as.numeric)))
#dat <- dat %>% arrange(desc(combined_score))
#count <- 0
#for (i in seq(nrow(dat))){
# if (dat$GeneID[i] %in% gsgo){
# count <- count +1
# if (count == r50){
# print(i)
# break
# }
# }
#}
de <- read.csv("Root_Atlas_DE_Gene_List.csv")
de <- de %>% arrange(pct.diff_rank) %>% arrange(avg_diff_rank)%>% arrange(myAUC_rank)%>% arrange(combined_rank)
## Remove those not present in the dataset
de <- de[!is.na(match(de$gene.ID,exptf)),]
head(de)
| myAUC | avg_diff | power | pct.1 | pct.2 | celltype | pseudotime.bin | gene.ID | gene.name | pct.diff | pct.diff_rank | avg_diff_rank | myAUC_rank | combined_rank | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | <chr> | <chr> | <dbl> | <int> | <int> | <int> | <int> | |
| 13 | 0.901 | 1.985825 | 0.802 | 0.959 | 0.287 | Endodermis | T4 | AT5G13910 | LEP | 0.672 | 2 | 4 | 1 | 1 |
| 40 | 0.934 | 2.820810 | 0.868 | 0.900 | 0.155 | Procambium | T0 | AT1G54690 | HTA3 | 0.745 | 2 | 35 | 2 | 1 |
| 51 | 0.841 | 2.351595 | 0.682 | 0.881 | 0.297 | Procambium | T1 | AT1G25560 | TEM1 | 0.584 | 1 | 11 | 3 | 1 |
| 58 | 0.979 | 3.799126 | 0.958 | 1.000 | 0.046 | Xylem | T1 | AT4G22680 | MYB85 | 0.954 | 1 | 7 | 4 | 1 |
| 63 | 0.945 | 4.666402 | 0.890 | 0.765 | 0.054 | Phloem | T2 | AT3G60530 | GATA4 | 0.711 | 35 | 1 | 5 | 1 |
| 66 | 0.871 | 2.623028 | 0.742 | 0.877 | 0.242 | Procambium | T2 | AT1G66600 | WRKY63 | 0.635 | 1 | 5 | 5 | 1 |
dat <- de %>% group_by(gene.ID) %>% reframe(combined_rank = mean(combined_rank),myAUC_rank = mean(myAUC_rank),pct.diff_rank = mean(pct.diff_rank),avg_diff_rank = mean(avg_diff_rank))
dat <- dat %>% arrange(combined_rank)
colnames(dat) <- c("GeneID","combined_rank","myAUC_rank","pct.diff_rank","avg_diff_rank")
head(dat)
| GeneID | combined_rank | myAUC_rank | pct.diff_rank | avg_diff_rank |
|---|---|---|---|---|
| <chr> | <dbl> | <dbl> | <dbl> | <dbl> |
| AT1G66600 | 6.500000 | 19.50000 | 23.00000 | 11.50000 |
| AT5G58010 | 8.333333 | 9.00000 | 7.00000 | 16.00000 |
| AT1G13600 | 9.500000 | 42.00000 | 34.50000 | 19.50000 |
| AT4G37260 | 12.333333 | 10.33333 | 20.33333 | 41.66667 |
| AT1G26680 | 13.000000 | 73.00000 | 37.00000 | 78.00000 |
| AT1G61660 | 13.000000 | 19.66667 | 17.33333 | 38.33333 |
de <- dat
run_r50_de <- function(x){
de$combined_score <- de[,grep(x,colnames(de))]
de <- de %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(de))){
if (de$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Expressed TFs permutation
R50_permutation <- c()
for (j in 1:1000){
ran <- sample(exptf, length(exptf), replace=FALSE)
count <- 0
for (i in seq(length(ran))){
if (ran[i] %in% gsgo){
count <- count +1
if (count == r50){
R50_permutation <- c(R50_permutation,i)
break
}
}
}
}
toplt <- data.frame(Methods=c("GeneSys degree centrality", "GeneSys out centrality", "GeneSys in centrality", "GeneSys betweenness centrality",
"GeneSys closeness centrality", "GeneSys eigenvector centrality","CellOracle degree centrality", "CellOracle out centrality",
"CellOracle in centrality", "CellOracle betweenness centrality", "CellOracle closeness centrality", "CellOracle eigenvector centrality",
"DE myAUC rank", "DE pct diff rank", "DE avg diff rank", "Expressed TFs permutation"),
R50=c(run_r50_genesys('degree_centrality'),run_r50_genesys('out_centrality'),run_r50_genesys('in_centrality'),
run_r50_genesys('betweenness_centrality'),run_r50_genesys('closeness_centrality'),run_r50_genesys('eigenvector_centrality'),
run_r50_celloracle('degree_centrality'),run_r50_celloracle('out_centrality'),run_r50_celloracle('in_centrality'),
run_r50_celloracle('betweenness_centrality'),run_r50_celloracle('closeness_centrality'),run_r50_celloracle('eigenvector_centrality'),
run_r50_de('myAUC_rank'),run_r50_de('pct.diff_rank'),run_r50_de('avg_diff_rank'), mean(R50_permutation)))
toplt
| Methods | R50 |
|---|---|
| <chr> | <dbl> |
| GeneSys degree centrality | 386.000 |
| GeneSys out centrality | 404.000 |
| GeneSys in centrality | 371.000 |
| GeneSys betweenness centrality | 367.000 |
| GeneSys closeness centrality | 735.000 |
| GeneSys eigenvector centrality | 461.000 |
| CellOracle degree centrality | 479.000 |
| CellOracle out centrality | 469.000 |
| CellOracle in centrality | 461.000 |
| CellOracle betweenness centrality | 413.000 |
| CellOracle closeness centrality | 505.000 |
| CellOracle eigenvector centrality | 488.000 |
| DE myAUC rank | 484.000 |
| DE pct diff rank | 495.000 |
| DE avg diff rank | 472.000 |
| Expressed TFs permutation | 750.213 |
options(repr.plot.width=8, repr.plot.height=8)
ggplot(toplt, aes(x=reorder(Methods, R50, decreasing = TRUE), y=R50)) + geom_point(size=4)+
labs(title="TF Prioritization Performance (R50)",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
toplt <- data.frame(Methods=factor(c(rep("GeneSys",6), rep("CellOracle",6), rep("DE",3), "Expressed TFs permutation"),
levels=c("Expressed TFs permutation", "DE", "CellOracle", "GeneSys")), R50=toplt$R50)
options(repr.plot.width=9.5, repr.plot.height=6)
ggplot(toplt, aes(x=Methods, y=R50))+
geom_boxplot(width=0.3)+
labs(title="TF Prioritization Performance (R50)",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
gsgo <- read.csv("./Gold_Standard_Root_TF_StringDB.csv", header=TRUE)
gsgo <- gsgo[which(gsgo[,5]=="Yes"),]
gsgo$preferredName
gsgo <- gsgo$GeneID
length(gsgo)
r50 <- 22
## Define genesys
run_r50_genesys <- function(x){
genesys$ct_score <- min_max_normalize(rowSums(apply(genesys[,grep(paste0('xyl_',x,'|phl_',x,'|pro_',x),colnames(genesys))],2,as.numeric)))
genesys$combined_score <- genesys$ct_score
genesys <- genesys %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(genesys))){
if (genesys$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Define celloracle
dat <- rbind(pro, xyl, phl)
## Remove those not present in the dataset
dat <- dat[!is.na(match(dat$X,exptf)),]
dat <- dat %>% group_by(cluster) %>% reframe(GeneID=X,degree_centrality = min_max_normalize(degree_centrality_all),
in_centrality = min_max_normalize(degree_centrality_in),
out_centrality = min_max_normalize(degree_centrality_out),
betweenness_centrality = min_max_normalize(betweenness_centrality),
closeness_centrality = min_max_normalize(closeness_centrality),
eigenvector_centrality = min_max_normalize(eigenvector_centrality))
dat <- dat %>% group_by(GeneID) %>% reframe(degree_centrality = sum(degree_centrality),
in_centrality = sum(in_centrality),
out_centrality = sum(out_centrality),
betweenness_centrality = sum(betweenness_centrality),
closeness_centrality = sum(closeness_centrality),
eigenvector_centrality = sum(eigenvector_centrality))
dat <- cbind(dat[,1],apply(dat[,2:7],2,min_max_normalize))
celloracle <- dat
run_r50_celloracle <- function(x){
celloracle$combined_score <- celloracle[,grep(x,colnames(celloracle))]
celloracle <- celloracle %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(celloracle))){
if (celloracle$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Define DE
de <- read.csv("Root_Atlas_DE_Gene_List.csv")
de <- de %>% filter(celltype=="Xylem"|celltype=="Phloem"|celltype=="Procambium")
## Remove those not present in the dataset
de <- de[!is.na(match(de$gene.ID,exptf)),]
dat <- de %>% group_by(gene.ID) %>% reframe(combined_rank = mean(combined_rank),myAUC_rank = mean(myAUC_rank),pct.diff_rank = mean(pct.diff_rank),avg_diff_rank = mean(avg_diff_rank))
dat <- dat %>% arrange(combined_rank)
colnames(dat) <- c("GeneID","combined_rank","myAUC_rank","pct.diff_rank","avg_diff_rank")
de <- dat
run_r50_de <- function(x){
de$combined_score <- de[,grep(x,colnames(de))]
de <- de %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(de))){
if (de$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Expressed TFs permutation
R50_permutation <- c()
for (j in 1:1000){
ran <- sample(exptf, length(exptf), replace=FALSE)
count <- 0
for (i in seq(length(ran))){
if (ran[i] %in% gsgo){
count <- count +1
if (count == r50){
R50_permutation <- c(R50_permutation,i)
break
}
}
}
}
toplt <- data.frame(Methods=c("GeneSys degree centrality", "GeneSys out centrality", "GeneSys in centrality", "GeneSys betweenness centrality",
"GeneSys closeness centrality", "GeneSys eigenvector centrality","CellOracle degree centrality", "CellOracle out centrality",
"CellOracle in centrality", "CellOracle betweenness centrality", "CellOracle closeness centrality", "CellOracle eigenvector centrality",
"DE myAUC rank", "DE pct diff rank", "DE avg diff rank", "Expressed TFs permutation"),
R50=c(run_r50_genesys('degree_centrality'),run_r50_genesys('out_centrality'),run_r50_genesys('in_centrality'),
run_r50_genesys('betweenness_centrality'),run_r50_genesys('closeness_centrality'),run_r50_genesys('eigenvector_centrality'),
run_r50_celloracle('degree_centrality'),run_r50_celloracle('out_centrality'),run_r50_celloracle('in_centrality'),
run_r50_celloracle('betweenness_centrality'),run_r50_celloracle('closeness_centrality'),run_r50_celloracle('eigenvector_centrality'),
run_r50_de('myAUC_rank'),run_r50_de('pct.diff_rank'),run_r50_de('avg_diff_rank'), mean(R50_permutation)))
toplt
| Methods | R50 |
|---|---|
| <chr> | <dbl> |
| GeneSys degree centrality | 99.000 |
| GeneSys out centrality | 173.000 |
| GeneSys in centrality | 95.000 |
| GeneSys betweenness centrality | 117.000 |
| GeneSys closeness centrality | 583.000 |
| GeneSys eigenvector centrality | 178.000 |
| CellOracle degree centrality | 288.000 |
| CellOracle out centrality | 255.000 |
| CellOracle in centrality | 190.000 |
| CellOracle betweenness centrality | 154.000 |
| CellOracle closeness centrality | 337.000 |
| CellOracle eigenvector centrality | 252.000 |
| DE myAUC rank | 275.000 |
| DE pct diff rank | 302.000 |
| DE avg diff rank | 245.000 |
| Expressed TFs permutation | 751.625 |
options(repr.plot.width=12, repr.plot.height=8)
ggplot(toplt, aes(x=reorder(Methods, R50, decreasing = TRUE), y=R50)) + geom_point(size=4)+
labs(title="Stele-specific TF Prioritization Performance (R50)",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
toplt <- data.frame(Methods=factor(c(rep("GeneSys",6), rep("CellOracle",6), rep("DE",3), "Expressed TFs permutation"),
levels=c("Expressed TFs permutation", "DE", "CellOracle", "GeneSys")), R50=toplt$R50)
options(repr.plot.width=9.5, repr.plot.height=6)
ggplot(toplt, aes(x=Methods, y=R50))+
geom_boxplot(width=0.3)+
labs(title="Stele-specific TF Prioritization Performance",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
gsgo <- read.csv("./Gold_Standard_Root_TF_StringDB.csv", header=TRUE)
gsgo <- gsgo[which(gsgo[,6]=="Yes"),]
gsgo$preferredName
gsgo <- gsgo$GeneID
length(gsgo)
r50 <- 24
## Define genesys
run_r50_genesys <- function(x){
genesys$ct_score <- min_max_normalize(rowSums(apply(genesys[,grep(paste0('atri_',x,'|tri_',x,'|lrc_',x),colnames(genesys))],2,as.numeric)))
genesys$combined_score <- genesys$ct_score
genesys <- genesys %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(genesys))){
if (genesys$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Define celloracle
dat <- rbind(atri, tri, lrc)
## Remove those not present in the dataset
dat <- dat[!is.na(match(dat$X,exptf)),]
dat <- dat %>% group_by(cluster) %>% reframe(GeneID=X,degree_centrality = min_max_normalize(degree_centrality_all),
in_centrality = min_max_normalize(degree_centrality_in),
out_centrality = min_max_normalize(degree_centrality_out),
betweenness_centrality = min_max_normalize(betweenness_centrality),
closeness_centrality = min_max_normalize(closeness_centrality),
eigenvector_centrality = min_max_normalize(eigenvector_centrality))
dat <- dat %>% group_by(GeneID) %>% reframe(degree_centrality = sum(degree_centrality),
in_centrality = sum(in_centrality),
out_centrality = sum(out_centrality),
betweenness_centrality = sum(betweenness_centrality),
closeness_centrality = sum(closeness_centrality),
eigenvector_centrality = sum(eigenvector_centrality))
dat <- cbind(dat[,1],apply(dat[,2:7],2,min_max_normalize))
celloracle <- dat
run_r50_celloracle <- function(x){
celloracle$combined_score <- celloracle[,grep(x,colnames(celloracle))]
celloracle <- celloracle %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(celloracle))){
if (celloracle$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Define DE
de <- read.csv("Root_Atlas_DE_Gene_List.csv")
de <- de %>% filter(celltype=="Atrichoblast"|celltype=="Trichoblast"|celltype=="Lateral Root Cap")
## Remove those not present in the dataset
de <- de[!is.na(match(de$gene.ID,exptf)),]
dat <- de %>% group_by(gene.ID) %>% reframe(combined_rank = mean(combined_rank),myAUC_rank = mean(myAUC_rank),pct.diff_rank = mean(pct.diff_rank),avg_diff_rank = mean(avg_diff_rank))
dat <- dat %>% arrange(combined_rank)
colnames(dat) <- c("GeneID","combined_rank","myAUC_rank","pct.diff_rank","avg_diff_rank")
de <- dat
run_r50_de <- function(x){
de$combined_score <- de[,grep(x,colnames(de))]
de <- de %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(de))){
if (de$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Expressed TFs permutation
R50_permutation <- c()
for (j in 1:1000){
ran <- sample(exptf, length(exptf), replace=FALSE)
count <- 0
for (i in seq(length(ran))){
if (ran[i] %in% gsgo){
count <- count +1
if (count == r50){
R50_permutation <- c(R50_permutation,i)
break
}
}
}
}
toplt <- data.frame(Methods=c("GeneSys degree centrality", "GeneSys out centrality", "GeneSys in centrality", "GeneSys betweenness centrality",
"GeneSys closeness centrality", "GeneSys eigenvector centrality","CellOracle degree centrality", "CellOracle out centrality",
"CellOracle in centrality", "CellOracle betweenness centrality", "CellOracle closeness centrality", "CellOracle eigenvector centrality",
"DE myAUC rank", "DE pct diff rank", "DE avg diff rank", "Expressed TFs permutation"),
R50=c(run_r50_genesys('degree_centrality'),run_r50_genesys('out_centrality'),run_r50_genesys('in_centrality'),
run_r50_genesys('betweenness_centrality'),run_r50_genesys('closeness_centrality'),run_r50_genesys('eigenvector_centrality'),
run_r50_celloracle('degree_centrality'),run_r50_celloracle('out_centrality'),run_r50_celloracle('in_centrality'),
run_r50_celloracle('betweenness_centrality'),run_r50_celloracle('closeness_centrality'),run_r50_celloracle('eigenvector_centrality'),
999,999,999, mean(R50_permutation)))
toplt
| Methods | R50 |
|---|---|
| <chr> | <dbl> |
| GeneSys degree centrality | 284.000 |
| GeneSys out centrality | 309.000 |
| GeneSys in centrality | 299.000 |
| GeneSys betweenness centrality | 284.000 |
| GeneSys closeness centrality | 324.000 |
| GeneSys eigenvector centrality | 254.000 |
| CellOracle degree centrality | 391.000 |
| CellOracle out centrality | 365.000 |
| CellOracle in centrality | 455.000 |
| CellOracle betweenness centrality | 304.000 |
| CellOracle closeness centrality | 351.000 |
| CellOracle eigenvector centrality | 392.000 |
| DE myAUC rank | 999.000 |
| DE pct diff rank | 999.000 |
| DE avg diff rank | 999.000 |
| Expressed TFs permutation | 728.913 |
options(repr.plot.width=12, repr.plot.height=8)
ggplot(toplt, aes(x=reorder(Methods, R50, decreasing = TRUE), y=R50)) + geom_point(size=4)+
labs(title="Epidermis-specific TF Prioritization Performance (R50)",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
toplt <- data.frame(Methods=factor(c(rep("GeneSys",6), rep("CellOracle",6), rep("DE",3), "Expressed TFs permutation"),
levels=c("DE","Expressed TFs permutation", "CellOracle", "GeneSys")), R50=toplt$R50)
options(repr.plot.width=9.5, repr.plot.height=6)
ggplot(toplt, aes(x=Methods, y=R50))+
geom_boxplot(width=0.3)+
labs(title="Epidermis-specific TF Prioritization Performance",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
gsgo <- read.csv("./Gold_Standard_Root_TF_StringDB.csv", header=TRUE)
gsgo <- gsgo[which(gsgo[,7]=="Yes"),]
gsgo$preferredName
gsgo <- gsgo$GeneID
length(gsgo)
r50 <- 15
## Define genesys
run_r50_genesys <- function(x){
genesys$ct_score <- min_max_normalize(rowSums(apply(genesys[,grep(paste0('xyl_',x),colnames(genesys))],2,as.numeric)))
genesys$combined_score <- genesys$ct_score
genesys <- genesys %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(genesys))){
if (genesys$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Define celloracle
dat <- rbind(xyl)
## Remove those not present in the dataset
dat <- dat[!is.na(match(dat$X,exptf)),]
dat <- dat %>% group_by(cluster) %>% reframe(GeneID=X,degree_centrality = min_max_normalize(degree_centrality_all),
in_centrality = min_max_normalize(degree_centrality_in),
out_centrality = min_max_normalize(degree_centrality_out),
betweenness_centrality = min_max_normalize(betweenness_centrality),
closeness_centrality = min_max_normalize(closeness_centrality),
eigenvector_centrality = min_max_normalize(eigenvector_centrality))
dat <- dat %>% group_by(GeneID) %>% reframe(degree_centrality = sum(degree_centrality),
in_centrality = sum(in_centrality),
out_centrality = sum(out_centrality),
betweenness_centrality = sum(betweenness_centrality),
closeness_centrality = sum(closeness_centrality),
eigenvector_centrality = sum(eigenvector_centrality))
dat <- cbind(dat[,1],apply(dat[,2:7],2,min_max_normalize))
celloracle <- dat
run_r50_celloracle <- function(x){
celloracle$combined_score <- celloracle[,grep(x,colnames(celloracle))]
celloracle <- celloracle %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(celloracle))){
if (celloracle$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Define DE
de <- read.csv("Root_Atlas_DE_Gene_List.csv")
de <- de %>% filter(celltype=="Xylem")
## Remove those not present in the dataset
de <- de[!is.na(match(de$gene.ID,exptf)),]
dat <- de %>% group_by(gene.ID) %>% reframe(combined_rank = mean(combined_rank),myAUC_rank = mean(myAUC_rank),pct.diff_rank = mean(pct.diff_rank),avg_diff_rank = mean(avg_diff_rank))
dat <- dat %>% arrange(combined_rank)
colnames(dat) <- c("GeneID","combined_rank","myAUC_rank","pct.diff_rank","avg_diff_rank")
de <- dat
run_r50_de <- function(x){
de$combined_score <- de[,grep(x,colnames(de))]
de <- de %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(de))){
if (de$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Expressed TFs permutation
R50_permutation <- c()
for (j in 1:1000){
ran <- sample(exptf, length(exptf), replace=FALSE)
count <- 0
for (i in seq(length(ran))){
if (ran[i] %in% gsgo){
count <- count +1
if (count == r50){
R50_permutation <- c(R50_permutation,i)
break
}
}
}
}
toplt <- data.frame(Methods=c("GeneSys degree centrality", "GeneSys out centrality", "GeneSys in centrality", "GeneSys betweenness centrality",
"GeneSys closeness centrality", "GeneSys eigenvector centrality","CellOracle degree centrality", "CellOracle out centrality",
"CellOracle in centrality", "CellOracle betweenness centrality", "CellOracle closeness centrality", "CellOracle eigenvector centrality",
"DE myAUC rank", "DE pct diff rank", "DE avg diff rank", "Expressed TFs permutation"),
R50=c(run_r50_genesys('degree_centrality'),run_r50_genesys('out_centrality'),run_r50_genesys('in_centrality'),
run_r50_genesys('betweenness_centrality'),run_r50_genesys('closeness_centrality'),run_r50_genesys('eigenvector_centrality'),
run_r50_celloracle('degree_centrality'),run_r50_celloracle('out_centrality'),run_r50_celloracle('in_centrality'),
run_r50_celloracle('betweenness_centrality'),run_r50_celloracle('closeness_centrality'),run_r50_celloracle('eigenvector_centrality'),
run_r50_de('myAUC_rank'),run_r50_de('pct.diff_rank'),run_r50_de('avg_diff_rank'), mean(R50_permutation)))
toplt
| Methods | R50 |
|---|---|
| <chr> | <dbl> |
| GeneSys degree centrality | 33.000 |
| GeneSys out centrality | 60.000 |
| GeneSys in centrality | 28.000 |
| GeneSys betweenness centrality | 74.000 |
| GeneSys closeness centrality | 49.000 |
| GeneSys eigenvector centrality | 53.000 |
| CellOracle degree centrality | 90.000 |
| CellOracle out centrality | 88.000 |
| CellOracle in centrality | 65.000 |
| CellOracle betweenness centrality | 50.000 |
| CellOracle closeness centrality | 135.000 |
| CellOracle eigenvector centrality | 62.000 |
| DE myAUC rank | 130.000 |
| DE pct diff rank | 133.000 |
| DE avg diff rank | 108.000 |
| Expressed TFs permutation | 723.006 |
options(repr.plot.width=12, repr.plot.height=8)
ggplot(toplt, aes(x=reorder(Methods, R50, decreasing = TRUE), y=R50)) + geom_point(size=4)+
labs(title="Xylem-specific TF Prioritization Performance (R50)",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
toplt <- data.frame(Methods=factor(c(rep("GeneSys",6), rep("CellOracle",6), rep("DE",3), "Expressed TFs permutation"),
levels=c("Expressed TFs permutation","DE", "CellOracle", "GeneSys")), R50=toplt$R50)
options(repr.plot.width=9.5, repr.plot.height=6)
ggplot(toplt, aes(x=Methods, y=R50))+
geom_boxplot(width=0.3)+
labs(title="Xylem-specific TF Prioritization Performance",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
gsgo <- read.csv("./Gold_Standard_Root_TF_StringDB.csv", header=TRUE)
gsgo <- gsgo[which(gsgo[,8]=="Yes"),]
gsgo$preferredName
gsgo <- gsgo$GeneID
length(gsgo)
r50 <- 18
## Define genesys
run_r50_genesys <- function(x){
genesys$ct_score <- min_max_normalize(rowSums(apply(genesys[,grep(paste0('^tri_',x),colnames(genesys))],2,as.numeric)))
genesys$combined_score <- genesys$ct_score
genesys <- genesys %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(genesys))){
if (genesys$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Define celloracle
dat <- rbind(tri)
## Remove those not present in the dataset
dat <- dat[!is.na(match(dat$X,exptf)),]
dat <- dat %>% group_by(cluster) %>% reframe(GeneID=X,degree_centrality = min_max_normalize(degree_centrality_all),
in_centrality = min_max_normalize(degree_centrality_in),
out_centrality = min_max_normalize(degree_centrality_out),
betweenness_centrality = min_max_normalize(betweenness_centrality),
closeness_centrality = min_max_normalize(closeness_centrality),
eigenvector_centrality = min_max_normalize(eigenvector_centrality))
dat <- dat %>% group_by(GeneID) %>% reframe(degree_centrality = sum(degree_centrality),
in_centrality = sum(in_centrality),
out_centrality = sum(out_centrality),
betweenness_centrality = sum(betweenness_centrality),
closeness_centrality = sum(closeness_centrality),
eigenvector_centrality = sum(eigenvector_centrality))
dat <- cbind(dat[,1],apply(dat[,2:7],2,min_max_normalize))
celloracle <- dat
run_r50_celloracle <- function(x){
celloracle$combined_score <- celloracle[,grep(x,colnames(celloracle))]
celloracle <- celloracle %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(celloracle))){
if (celloracle$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Define DE
de <- read.csv("Root_Atlas_DE_Gene_List.csv")
de <- de %>% filter(celltype=="Trichoblast")
## Remove those not present in the dataset
de <- de[!is.na(match(de$gene.ID,exptf)),]
dat <- de %>% group_by(gene.ID) %>% reframe(combined_rank = mean(combined_rank),myAUC_rank = mean(myAUC_rank),pct.diff_rank = mean(pct.diff_rank),avg_diff_rank = mean(avg_diff_rank))
dat <- dat %>% arrange(combined_rank)
colnames(dat) <- c("GeneID","combined_rank","myAUC_rank","pct.diff_rank","avg_diff_rank")
de <- dat
run_r50_de <- function(x){
de$combined_score <- de[,grep(x,colnames(de))]
de <- de %>% arrange(desc(combined_score))
count <- 0
for (i in seq(nrow(de))){
if (de$GeneID[i] %in% gsgo){
count <- count +1
if (count == r50){
return(i)
break
}
}
}
}
## Expressed TFs permutation
R50_permutation <- c()
for (j in 1:1000){
ran <- sample(exptf, length(exptf), replace=FALSE)
count <- 0
for (i in seq(length(ran))){
if (ran[i] %in% gsgo){
count <- count +1
if (count == r50){
R50_permutation <- c(R50_permutation,i)
break
}
}
}
}
toplt <- data.frame(Methods=c("GeneSys degree centrality", "GeneSys out centrality", "GeneSys in centrality", "GeneSys betweenness centrality",
"GeneSys closeness centrality", "GeneSys eigenvector centrality","CellOracle degree centrality", "CellOracle out centrality",
"CellOracle in centrality", "CellOracle betweenness centrality", "CellOracle closeness centrality", "CellOracle eigenvector centrality",
"DE myAUC rank", "DE pct diff rank", "DE avg diff rank", "Expressed TFs permutation"),
R50=c(run_r50_genesys('degree_centrality'),run_r50_genesys('out_centrality'),run_r50_genesys('in_centrality'),
run_r50_genesys('betweenness_centrality'),run_r50_genesys('closeness_centrality'),run_r50_genesys('eigenvector_centrality'),
run_r50_celloracle('degree_centrality'),run_r50_celloracle('out_centrality'),run_r50_celloracle('in_centrality'),
run_r50_celloracle('betweenness_centrality'),run_r50_celloracle('closeness_centrality'),run_r50_celloracle('eigenvector_centrality'),
999,999,999, mean(R50_permutation)))
toplt
| Methods | R50 |
|---|---|
| <chr> | <dbl> |
| GeneSys degree centrality | 189.000 |
| GeneSys out centrality | 217.000 |
| GeneSys in centrality | 212.000 |
| GeneSys betweenness centrality | 262.000 |
| GeneSys closeness centrality | 271.000 |
| GeneSys eigenvector centrality | 194.000 |
| CellOracle degree centrality | 508.000 |
| CellOracle out centrality | 476.000 |
| CellOracle in centrality | 425.000 |
| CellOracle betweenness centrality | 339.000 |
| CellOracle closeness centrality | 449.000 |
| CellOracle eigenvector centrality | 501.000 |
| DE myAUC rank | 999.000 |
| DE pct diff rank | 999.000 |
| DE avg diff rank | 999.000 |
| Expressed TFs permutation | 723.495 |
options(repr.plot.width=12, repr.plot.height=8)
ggplot(toplt, aes(x=reorder(Methods, R50, decreasing = TRUE), y=R50)) + geom_point(size=4)+
labs(title="Trichoblast-specific TF Prioritization Performance (R50)",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
toplt <- data.frame(Methods=factor(c(rep("GeneSys",6), rep("CellOracle",6), rep("DE",3), "Expressed TFs permutation"),
levels=c("DE","Expressed TFs permutation", "CellOracle", "GeneSys")), R50=toplt$R50)
options(repr.plot.width=9.5, repr.plot.height=6)
ggplot(toplt, aes(x=Methods, y=R50))+
geom_boxplot(width=0.3)+
labs(title="Trichoblast-specific TF Prioritization Performance",x="", y = "R50")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
dat <- genesys
plot_heatmap <- function(gene, centrality){
sub <- as.numeric(t(dat[which(dat$TF==gene),grep(centrality,colnames(dat))]))
sub <- as.matrix(cbind(sub[1:10],sub[11:20],sub[21:30],sub[31:40],sub[41:50]))
## Cell types
rownames(sub) <- c('Atrichoblast','Trichoblast','LRC','Cortex','Endodermis','Pericycle','Procambium','Xylem','Phloem','Columella')
## Transition
colnames(sub) <- c('t0-t1', 't1-t3', 't3-t5', 't5-t7', 't7-t9')
# Reorder rows
sub <- sub[c(8,9,7,6,5,4,2,1,3,10),]
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
Heatmap(sub, rect_gp = gpar(col = "white", lwd = 1) , show_heatmap_legend = TRUE, name = paste0(gene,"\n","weighted","\n","network","\n","centrality"),
col = col_fun, column_title = paste0(str_split_i(centrality,"_",1),"\n",str_split_i(centrality,"_",2)), column_title_gp = gpar(fontsize = 12, fontface = "bold"),
cluster_rows = FALSE, cluster_columns = FALSE,
show_column_names = FALSE, bottom_annotation = HeatmapAnnotation(
text = anno_text(colnames(sub), rot = 60, location = unit(1, "npc"), just = "right"))
)
}
plot_heatmap2 <- function(gene, centrality){
sub <- as.numeric(t(dat[which(dat$TF==gene),grep(centrality,colnames(dat))]))
sub <- as.matrix(cbind(sub[1:10],sub[11:20],sub[21:30],sub[31:40],sub[41:50]))
## Cell types
rownames(sub) <- c('Atrichoblast','Trichoblast','LRC','Cortex','Endodermis','Pericycle','Procambium','Xylem','Phloem','Columella')
## Transition
colnames(sub) <- c('t0-t1', 't1-t3', 't3-t5', 't5-t7', 't7-t9')
# Reorder rows
sub <- sub[c(8,9,7,6,5,4,2,1,3,10),]
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
Heatmap(sub, rect_gp = gpar(col = "white", lwd = 1) , show_heatmap_legend = FALSE,
col = col_fun, column_title = "out degree \n centrality", column_title_gp = gpar(fontsize = 12, fontface = "bold"),
cluster_rows = FALSE, cluster_columns = FALSE,
show_column_names = FALSE, bottom_annotation = HeatmapAnnotation(
text = anno_text(colnames(sub), rot = 60, location = unit(1, "npc"), just = "right"))
)
}
plot_heatmap3 <- function(gene, centrality){
sub <- as.numeric(t(dat[which(dat$TF==gene),grep(centrality,colnames(dat))]))
sub <- as.matrix(cbind(sub[1:10],sub[11:20],sub[21:30],sub[31:40],sub[41:50]))
## Cell types
rownames(sub) <- c('Atrichoblast','Trichoblast','LRC','Cortex','Endodermis','Pericycle','Procambium','Xylem','Phloem','Columella')
## Transition
colnames(sub) <- c('t0-t1', 't1-t3', 't3-t5', 't5-t7', 't7-t9')
# Reorder rows
sub <- sub[c(8,9,7,6,5,4,2,1,3,10),]
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
Heatmap(sub, rect_gp = gpar(col = "white", lwd = 1), name = paste0("unweighted","\n","network","\n","centrality"),
col = col_fun, column_title = "in degree \n centrality", column_title_gp = gpar(fontsize = 12, fontface = "bold"),
cluster_rows = FALSE, cluster_columns = FALSE,
show_column_names = FALSE, bottom_annotation = HeatmapAnnotation(
text = anno_text(colnames(sub), rot = 60, location = unit(1, "npc"), just = "right"))
)
}
plot_all_centrality <- function(gene){
options(repr.plot.width=10, repr.plot.height=6)
plot_heatmap(gene,"betweenness_centrality") + plot_heatmap2(gene,"out_centrality") + plot_heatmap3(gene,"in_centrality")
}
plot_all_centrality("TTG1")
plot_all_centrality("CPC")
plot_all_centrality("SHR")
plot_all_centrality("SCR")
plot_all_centrality("BLJ")
plot_all_centrality("JKD")
plot_all_centrality("MYB36")
plot_all_centrality("RVN")
plot_all_centrality("MGP")
plot_all_centrality("NUC")
plot_all_centrality("WER")
## HAT7
plot_all_centrality("HAT7")
## GATA10
plot_all_centrality("GATA10")
## GATA11
plot_all_centrality("GATA11")
plot_all_centrality("AN3")
plot_all_centrality("GL2")
plot_all_centrality("LBD15")
plot_all_centrality <- function(gene){
options(repr.plot.width=8, repr.plot.height=4)
plot_heatmap(gene,"betweenness_centrality") + plot_heatmap2(gene,"out_centrality") + plot_heatmap3(gene,"in_centrality")
}
plot_all_centrality("SHR")
plot_all_centrality("WER")
plot_bc <- function(gene){
sub <- as.numeric(t(dat[which(dat$TF==gene),grep("betweenness_centrality",colnames(dat))]))
sub <- as.matrix(cbind(sub[1:10],sub[11:20],sub[21:30],sub[31:40],sub[41:50]))
## Cell types
rownames(sub) <- c('Atrichoblast','Trichoblast','LRC','Cortex','Endodermis','Pericycle','Procambium','Xylem','Phloem','Columella')
## Transition
colnames(sub) <- c('t0-t1', 't1-t3', 't3-t5', 't5-t7', 't7-t9')
# Reorder rows
sub <- sub[c(8,9,7,6,5,4,2,1,3,10),]
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
Heatmap(sub, rect_gp = gpar(col = "white", lwd = 1) , show_heatmap_legend = FALSE,
col = col_fun, column_title = gene, column_title_gp = gpar(fontsize = 12, fontface = "bold"),
cluster_rows = FALSE, cluster_columns = FALSE,
show_column_names = FALSE, bottom_annotation = HeatmapAnnotation(
text = anno_text(colnames(sub), rot = 60, location = unit(1, "npc"), just = "right"))
)
}
plot_oc <- function(gene){
sub <- as.numeric(t(dat[which(dat$TF==gene),grep("out_centrality",colnames(dat))]))
sub <- as.matrix(cbind(sub[1:10],sub[11:20],sub[21:30],sub[31:40],sub[41:50]))
## Cell types
rownames(sub) <- c('Atrichoblast','Trichoblast','LRC','Cortex','Endodermis','Pericycle','Procambium','Xylem','Phloem','Columella')
## Transition
colnames(sub) <- c('t0-t1', 't1-t3', 't3-t5', 't5-t7', 't7-t9')
# Reorder rows
sub <- sub[c(8,9,7,6,5,4,2,1,3,10),]
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
Heatmap(sub, rect_gp = gpar(col = "white", lwd = 1) , show_heatmap_legend = FALSE,
col = col_fun, column_title = gene, column_title_gp = gpar(fontsize = 12, fontface = "bold"),
cluster_rows = FALSE, cluster_columns = FALSE,
show_column_names = FALSE, bottom_annotation = HeatmapAnnotation(
text = anno_text(colnames(sub), rot = 60, location = unit(1, "npc"), just = "right"))
)
}
plot_ic <- function(gene){
sub <- as.numeric(t(dat[which(dat$TF==gene),grep("in_centrality",colnames(dat))]))
sub <- as.matrix(cbind(sub[1:10],sub[11:20],sub[21:30],sub[31:40],sub[41:50]))
## Cell types
rownames(sub) <- c('Atrichoblast','Trichoblast','LRC','Cortex','Endodermis','Pericycle','Procambium','Xylem','Phloem','Columella')
## Transition
colnames(sub) <- c('t0-t1', 't1-t3', 't3-t5', 't5-t7', 't7-t9')
# Reorder rows
sub <- sub[c(8,9,7,6,5,4,2,1,3,10),]
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
Heatmap(sub, rect_gp = gpar(col = "white", lwd = 1) , show_heatmap_legend = FALSE,
col = col_fun, column_title = gene, column_title_gp = gpar(fontsize = 12, fontface = "bold"),
cluster_rows = FALSE, cluster_columns = FALSE,
show_column_names = FALSE, bottom_annotation = HeatmapAnnotation(
text = anno_text(colnames(sub), rot = 60, location = unit(1, "npc"), just = "right"))
)
}
plot_dc <- function(gene){
sub <- as.numeric(t(dat[which(dat$TF==gene),grep("degree_centrality",colnames(dat))]))
sub <- as.matrix(cbind(sub[1:10],sub[11:20],sub[21:30],sub[31:40],sub[41:50]))
## Cell types
rownames(sub) <- c('Atrichoblast','Trichoblast','LRC','Cortex','Endodermis','Pericycle','Procambium','Xylem','Phloem','Columella')
## Transition
colnames(sub) <- c('t0-t1', 't1-t3', 't3-t5', 't5-t7', 't7-t9')
# Reorder rows
sub <- sub[c(8,9,7,6,5,4,2,1,3,10),]
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
Heatmap(sub, rect_gp = gpar(col = "white", lwd = 1) , show_heatmap_legend = FALSE,
col = col_fun, column_title = gene, column_title_gp = gpar(fontsize = 12, fontface = "bold"),
cluster_rows = FALSE, cluster_columns = FALSE,
show_column_names = FALSE, bottom_annotation = HeatmapAnnotation(
text = anno_text(colnames(sub), rot = 60, location = unit(1, "npc"), just = "right"))
)
}
plot_blank <- function(gene){
sub <- as.numeric(t(dat[which(dat$TF==gene),grep("betweenness_centrality",colnames(dat))]))
sub <- as.matrix(cbind(sub[1:10],sub[11:20],sub[21:30],sub[31:40],sub[41:50]))
## Cell types
rownames(sub) <- c('Atrichoblast','Trichoblast','LRC','Cortex','Endodermis','Pericycle','Procambium','Xylem','Phloem','Columella')
## Transition
colnames(sub) <- c('t0-t1', 't1-t3', 't3-t5', 't5-t7', 't7-t9')
# Reorder rows
sub <- sub[c(8,9,7,6,5,4,2,1,3,10),]
col_fun = colorRamp2(c(0, 0.001, 1), c('white',"white", "white"))
Heatmap(sub, rect_gp = gpar(col = "white", lwd = 1) , show_heatmap_legend = FALSE,
col = col_fun, column_title_gp = gpar(fontsize = 12, fontface = "bold"),
cluster_rows = FALSE, cluster_columns = FALSE,
show_column_names = FALSE, show_row_names = TRUE
)
}
# Combine the top three centralies
sub <- dat[,grep("betweenness_centrality|in_centrality|out_centrality",colnames(dat))]
sub <- as.data.frame(sapply(sub, as.numeric))
rownames(sub) <- dat$TF
head(sub)
| atri_out_centrality_1 | atri_in_centrality_1 | atri_betweenness_centrality_1 | tri_out_centrality_1 | tri_in_centrality_1 | tri_betweenness_centrality_1 | lrc_out_centrality_1 | lrc_in_centrality_1 | lrc_betweenness_centrality_1 | cor_out_centrality_1 | ... | pro_betweenness_centrality_5 | xyl_out_centrality_5 | xyl_in_centrality_5 | xyl_betweenness_centrality_5 | phl_out_centrality_5 | phl_in_centrality_5 | phl_betweenness_centrality_5 | col_out_centrality_5 | col_in_centrality_5 | col_betweenness_centrality_5 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | ... | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| BZIP9 | 0.0000000 | 0.0000000 | 0.000000 | 0.00000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.000000000 | ... | 0.9210677 | 0 | 0 | 0 | 0.8440367 | 0.8463303 | 0.2032263 | 0.00000000 | 0.000000000 | 0 |
| AT3G43430 | 0.0000000 | 0.0000000 | 0.000000 | 0.00000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.002673797 | ... | 0.5052969 | 0 | 0 | 0 | 0.2350917 | 0.1089450 | 0.1105647 | 0.00000000 | 0.000000000 | 0 |
| PLT1 | 0.2160494 | 0.5653710 | 0.963923 | 0.00000000 | 0.0000000 | 0.0000000 | 0.1568627 | 1.0000000 | 0.9868855 | 0.385026738 | ... | 0.0000000 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.0000000 | 0.09975669 | 0.002207506 | 0 |
| HAT7 | 0.0000000 | 0.0000000 | 0.000000 | 0.05179283 | 0.3275862 | 0.8317337 | 0.0000000 | 0.0000000 | 0.0000000 | 0.024064171 | ... | 0.0000000 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.0000000 | 0.00000000 | 0.000000000 | 0 |
| MYB36 | 0.0000000 | 0.0000000 | 0.000000 | 0.00000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.0000000 | 0.114973262 | ... | 0.0000000 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.0000000 | 0.00000000 | 0.000000000 | 0 |
| GATA2 | 0.7932099 | 0.5759717 | 0.804800 | 0.66533865 | 0.5905172 | 0.8920287 | 0.8591800 | 0.9802513 | 1.0000000 | 0.553475936 | ... | 0.0000000 | 0 | 0 | 0 | 0.0000000 | 0.0000000 | 0.0000000 | 0.00000000 | 0.000000000 | 0 |
bc_rank <- data.frame(all=rowSums(sub),atri=rowSums(sub[,grep("^atri_",colnames(sub))]),tri=rowSums(sub[,grep("^tri_",colnames(sub))])
,cor=rowSums(sub[,grep("^cor_",colnames(sub))]),end=rowSums(sub[,grep("^end_",colnames(sub))])
,per=rowSums(sub[,grep("^per_",colnames(sub))]),pro=rowSums(sub[,grep("^pro_",colnames(sub))])
,xyl=rowSums(sub[,grep("^xyl_",colnames(sub))]),phl=rowSums(sub[,grep("^phl_",colnames(sub))])
,lrc=rowSums(sub[,grep("^lrc_",colnames(sub))]),col=rowSums(sub[,grep("^col_",colnames(sub))]))
bc_rank$GeneID <- wanted_TFs$GeneID[match(rownames(bc_rank),wanted_TFs$Name)]
head(bc_rank)
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | |
| BZIP9 | 31.42213 | 0.000000 | 0.000000 | 0.00000000 | 0.005736138 | 8.55316613 | 11.88088107 | 0.02003315 | 10.9623184 | 0.000000 | 0.000000 | AT5G24800 |
| AT3G43430 | 29.05965 | 0.000000 | 0.000000 | 0.00544388 | 0.029360833 | 9.20656526 | 11.24626128 | 1.83863137 | 6.7333880 | 0.000000 | 0.000000 | AT3G43430 |
| PLT1 | 23.97514 | 3.940608 | 0.000000 | 2.00953127 | 1.492057686 | 0.05699842 | 0.00000000 | 0.00000000 | 0.0000000 | 9.148008 | 7.327940 | AT3G20840 |
| HAT7 | 33.13977 | 6.200914 | 5.547329 | 8.04274907 | 5.877125010 | 1.24427942 | 0.00000000 | 0.00000000 | 0.0122843 | 4.284922 | 1.930171 | AT5G15150 |
| MYB36 | 20.57418 | 0.000000 | 0.000000 | 6.29093689 | 10.748544272 | 3.53469871 | 0.00000000 | 0.00000000 | 0.0000000 | 0.000000 | 0.000000 | AT5G57620 |
| GATA2 | 33.12273 | 6.623792 | 6.596557 | 2.46621779 | 2.051664424 | 0.80375905 | 0.03881894 | 0.09406244 | 0.1559529 | 12.103509 | 2.188393 | AT2G45050 |
atri_rank <- bc_rank[which(bc_rank$atri*2 > bc_rank$all),]%>% arrange(desc(atri))
atri_rank$GeneName <- rownames(atri_rank)
atri_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| MYB23 | 16.31793255 | 8.20713964 | 3.311916916 | 1.435215442 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 3.216075778 | 0.147584780 | AT5G40330 | MYB23 |
| GL2 | 12.59879540 | 7.07284877 | 3.606946457 | 0.121283719 | 0.126559384 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.671157066 | 0.000000000 | AT1G79840 | GL2 |
| TTG2 | 9.80635891 | 6.93096555 | 2.295746399 | 0.043262180 | 0.031031246 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.505353540 | 0.000000000 | AT2G37260 | TTG2 |
| MYB45 | 7.74054316 | 5.00001186 | 1.548317405 | 1.105903099 | 0.032240503 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.054070289 | 0.000000000 | AT3G48920 | MYB45 |
| IAA14 | 8.69681235 | 4.86976717 | 2.350063082 | 0.057152540 | 0.000000000 | 0.167830167 | 0.486865950 | 0.168121035 | 0.006276239 | 0.549981601 | 0.040754561 | AT4G14550 | IAA14 |
| WRKY45 | 5.28282187 | 4.52127277 | 0.662200395 | 0.028887457 | 0.005736138 | 0.004460176 | 0.000000000 | 0.000000000 | 0.000000000 | 0.045499150 | 0.014765782 | AT3G01970 | WRKY45 |
| ARR6 | 6.83180069 | 3.82931392 | 1.604692837 | 0.145406277 | 0.091157087 | 0.142688889 | 0.192916368 | 0.206112299 | 0.068509068 | 0.263100941 | 0.287903003 | AT5G62920 | ARR6 |
| CRF4 | 6.17032329 | 3.58350854 | 1.213204139 | 0.590897376 | 0.216926392 | 0.051316603 | 0.000000000 | 0.000000000 | 0.000000000 | 0.475292500 | 0.039177743 | AT4G27950 | CRF4 |
| AT2G28710 | 3.60999396 | 3.21999351 | 0.304157050 | 0.000000000 | 0.007648184 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.078195215 | 0.000000000 | AT2G28710 | AT2G28710 |
| NAC6 | 3.86309350 | 2.92448703 | 0.595094653 | 0.000000000 | 0.054940125 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.288571683 | 0.000000000 | AT5G39610 | NAC6 |
| MYB50 | 5.35178146 | 2.75139760 | 0.503140568 | 0.059817338 | 0.000000000 | 0.000000000 | 0.137683480 | 1.872933038 | 0.026809435 | 0.000000000 | 0.000000000 | AT1G57560 | MYB50 |
| FIT | 4.32726936 | 2.73484046 | 0.720809085 | 0.000000000 | 0.028669678 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.767557913 | 0.075392220 | AT2G28160 | FIT |
| WRKY27 | 4.76095235 | 2.51398738 | 0.660387042 | 0.059208675 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.467623124 | 0.059746125 | AT5G52830 | WRKY27 |
| HB17 | 4.33177254 | 2.47505819 | 1.259045691 | 0.000000000 | 0.002868069 | 0.000000000 | 0.007639326 | 0.587161264 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G01430 | HB17 |
| AT3G05860 | 2.75994367 | 1.88069000 | 0.866575597 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.012678080 | 0.000000000 | AT3G05860 | AT3G05860 |
| OFP18 | 2.11012124 | 1.84270868 | 0.225334328 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.042078228 | 0.000000000 | AT3G52540 | OFP18 |
| LBD25 | 2.55363820 | 1.61563577 | 0.025062145 | 0.743786235 | 0.012198036 | 0.119627597 | 0.037328418 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G27650 | LBD25 |
| NAC044 | 2.74052836 | 1.53785196 | 0.185048913 | 0.095316041 | 0.213034297 | 0.630820177 | 0.000000000 | 0.000000000 | 0.000000000 | 0.078456974 | 0.000000000 | AT3G01600 | NAC044 |
| RMR1 | 1.99874239 | 1.45886013 | 0.043433252 | 0.080247076 | 0.115541829 | 0.032785470 | 0.134617232 | 0.026320342 | 0.075999734 | 0.000000000 | 0.030937316 | AT5G66160 | RMR1 |
| NAC003 | 2.32762624 | 1.40760202 | 0.311770468 | 0.353506885 | 0.059890914 | 0.071963621 | 0.052664353 | 0.048429810 | 0.000000000 | 0.000000000 | 0.021798166 | AT1G02220 | NAC003 |
| KAN | 2.20987712 | 1.27353492 | 0.322695691 | 0.121476291 | 0.023721770 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.385566914 | 0.082881531 | AT5G16560 | KAN |
| AT5G22890 | 1.36913636 | 1.14378922 | 0.206470408 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.018876724 | AT5G22890 | AT5G22890 |
| HB30 | 1.27288069 | 1.09275226 | 0.006587797 | 0.000000000 | 0.002868069 | 0.025097682 | 0.000000000 | 0.041624158 | 0.007747006 | 0.096203717 | 0.000000000 | AT5G15210 | HB30 |
| WRKY47 | 1.65831084 | 1.07182034 | 0.212405427 | 0.120534320 | 0.253550750 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G01720 | WRKY47 |
| PTF1 | 1.69335729 | 1.01681850 | 0.130021628 | 0.245983102 | 0.255931767 | 0.000000000 | 0.008178273 | 0.000000000 | 0.036424023 | 0.000000000 | 0.000000000 | AT3G02150 | PTF1 |
| AT2G18670 | 1.45742465 | 0.79056754 | 0.343466303 | 0.229416723 | 0.021959243 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.032673780 | 0.039341067 | AT2G18670 | AT2G18670 |
| HB24 | 1.25568687 | 0.77531120 | 0.216848330 | 0.003880024 | 0.000000000 | 0.040533963 | 0.193332105 | 0.007524815 | 0.004456859 | 0.013799569 | 0.000000000 | AT2G18350 | HB24 |
| AT4G31650 | 0.55219987 | 0.40261254 | 0.092706568 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.056880762 | 0.000000000 | AT4G31650 | AT4G31650 |
| HSFB3 | 0.39912209 | 0.37453625 | 0.024585844 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G41690 | HSFB3 |
| GIS3 | 0.47235893 | 0.32971951 | 0.142639415 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G68360 | GIS3 |
| NAC069 | 0.53796818 | 0.29079612 | 0.098868360 | 0.000000000 | 0.002868069 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.042125364 | 0.103310267 | AT4G01550 | NAC069 |
| MEA | 0.29503532 | 0.25268757 | 0.007985591 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.034362168 | 0.000000000 | AT1G02580 | MEA |
| AT4G01350 | 0.38758173 | 0.23189368 | 0.100963743 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.048464513 | 0.006259796 | AT4G01350 | AT4G01350 |
| NLP4 | 0.27856383 | 0.19051177 | 0.055025405 | 0.000000000 | 0.002868069 | 0.000000000 | 0.000000000 | 0.000000000 | 0.030158584 | 0.000000000 | 0.000000000 | AT1G20640 | NLP4 |
| AT1G11490 | 0.21912705 | 0.16563057 | 0.045739637 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.007756839 | 0.000000000 | AT1G11490 | AT1G11490 |
| PHE1 | 0.12111551 | 0.11318570 | 0.007929803 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G65330 | PHE1 |
| AT4G18110 | 0.07830247 | 0.07830247 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G18110 | AT4G18110 |
| AT1G14600 | 0.08088867 | 0.07228446 | 0.000000000 | 0.000000000 | 0.008604207 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G14600 | AT1G14600 |
| WRKY13 | 0.04582144 | 0.04582144 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G39410 | WRKY13 |
| LBD26 | 0.06567464 | 0.04082963 | 0.011156338 | 0.007722008 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.005966671 | 0.000000000 | AT3G27940 | LBD26 |
| AT3G07260 | 0.07593283 | 0.03971993 | 0.000000000 | 0.000000000 | 0.036212897 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G07260 | AT3G07260 |
| AT4G38070 | 0.04134166 | 0.02628935 | 0.008360148 | 0.000000000 | 0.006692161 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G38070 | AT4G38070 |
| AT3G13840 | 0.01119403 | 0.01119403 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G13840 | AT3G13840 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(atri_rank[1:10,], aes(x=reorder(GeneName, atri, decreasing = FALSE), y=atri)) + geom_point(size=4)+
labs(title="Atrichoblast-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(atri_rank,"Atrichoblast_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- atri_rank %>% rownames(.)
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Atrichoblast ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
q1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3])
q2 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3])
q3 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3])
q1 <- grid.grabExpr(draw(q1))
q2 <- grid.grabExpr(draw(q2))
q3 <- grid.grabExpr(draw(q3))
options(repr.plot.width=6, repr.plot.height=8)
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q1,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q2,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q3,nrow=2,rel_heights = c(1, 8)),nrow=3)
tri_rank <- bc_rank[which(bc_rank$tri*2 > bc_rank$all),]%>% arrange(desc(tri))
tri_rank$GeneName <- rownames(tri_rank)
tri_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| AT3G53370 | 10.703067482 | 1.809742147 | 8.309677470 | 0.000000000 | 0.000000000 | 0.162668647 | 0.05408138 | 0.325731713 | 0.041166121 | 0.000000000 | 0.000000000 | AT3G53370 | AT3G53370 |
| LRL3 | 11.471484177 | 3.379461231 | 8.092022945 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G58010 | LRL3 |
| RHD6 | 10.231879434 | 3.043919316 | 7.187960117 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G66470 | RHD6 |
| AT4G09100 | 5.319501634 | 0.236489354 | 5.083012279 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G09100 | AT4G09100 |
| RSL4 | 5.167261070 | 0.110264729 | 5.056996342 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G27740 | RSL4 |
| RSL2 | 4.524441211 | 0.051378954 | 4.473062258 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G33880 | RSL2 |
| RAP2.11 | 3.210204477 | 0.000000000 | 3.197663118 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.012541359 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G19790 | RAP2.11 |
| AT4G39160 | 3.554318032 | 0.223674563 | 3.189048364 | 0.000000000 | 0.012428298 | 0.004384828 | 0.02017415 | 0.000000000 | 0.047321292 | 0.009035242 | 0.048251301 | AT4G39160 | AT4G39160 |
| AT5G56200 | 3.181772719 | 0.000000000 | 3.181772719 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G56200 | AT5G56200 |
| AT2G37120 | 5.044905135 | 0.828925741 | 2.583107573 | 0.055263384 | 0.156456222 | 0.179113807 | 0.01628388 | 0.974156109 | 0.118228679 | 0.129591337 | 0.003778406 | AT2G37120 | AT2G37120 |
| ESE3 | 2.683309001 | 0.119329105 | 2.206075220 | 0.205807146 | 0.142115650 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.009981880 | AT5G25190 | ESE3 |
| WRKY61 | 4.259870565 | 2.109937239 | 2.149933326 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G18860 | WRKY61 |
| AT5G06800 | 2.866448697 | 1.077281362 | 1.737509465 | 0.000000000 | 0.012987961 | 0.005909557 | 0.00000000 | 0.000000000 | 0.032760352 | 0.000000000 | 0.000000000 | AT5G06800 | AT5G06800 |
| WRKY70 | 2.616735517 | 0.362206667 | 1.543605842 | 0.000000000 | 0.000000000 | 0.073952273 | 0.36791832 | 0.018263683 | 0.003339541 | 0.130639555 | 0.116809634 | AT3G56400 | WRKY70 |
| RL6 | 1.533961941 | 0.000000000 | 1.533961941 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G75250 | RL6 |
| WRKY72 | 2.631209313 | 0.397527208 | 1.330070167 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.717404861 | 0.186207077 | AT5G15130 | WRKY72 |
| GL3 | 1.264223940 | 0.268798576 | 0.978997438 | 0.016427926 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G41315 | GL3 |
| AT1G61990 | 1.646543329 | 0.308764613 | 0.924735513 | 0.107070378 | 0.121099269 | 0.107694175 | 0.04423033 | 0.002508272 | 0.000000000 | 0.019692759 | 0.010748023 | AT1G61990 | AT1G61990 |
| TAFII15 | 1.499091664 | 0.057474093 | 0.761413981 | 0.003880024 | 0.031248686 | 0.132966342 | 0.14326205 | 0.204642632 | 0.155406349 | 0.000000000 | 0.008797508 | AT4G31720 | TAFII15 |
| AT2G05160 | 0.724767538 | 0.054812165 | 0.662710899 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.007244474 | 0.000000000 | 0.000000000 | AT2G05160 | AT2G05160 |
| AT2G20030 | 0.700484313 | 0.073484201 | 0.627000112 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G20030 | AT2G20030 |
| AT5G04390 | 0.592985046 | 0.003731343 | 0.577765006 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.011488697 | AT5G04390 | AT5G04390 |
| MC2 | 1.031987270 | 0.456245534 | 0.575741737 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G25110 | MC2 |
| WRKY42 | 1.095053422 | 0.181274511 | 0.565437156 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.248962871 | 0.099378883 | AT4G04450 | WRKY42 |
| SUVR4 | 0.382088900 | 0.013690228 | 0.294552531 | 0.011583012 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.022498765 | 0.039764365 | AT3G04380 | SUVR4 |
| AT3G22560 | 0.361986289 | 0.106681072 | 0.255305218 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G22560 | AT3G22560 |
| RAD54 | 0.280632949 | 0.000000000 | 0.155946722 | 0.032181848 | 0.000000000 | 0.011397451 | 0.00000000 | 0.000000000 | 0.000000000 | 0.069112527 | 0.011994401 | AT3G19210 | RAD54 |
| MYB47 | 0.258138935 | 0.109314549 | 0.141176202 | 0.000000000 | 0.007648184 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G18710 | MYB47 |
| EIL2 | 0.138109082 | 0.000000000 | 0.138109082 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G21120 | EIL2 |
| AT2G14760 | 0.131975607 | 0.000000000 | 0.131975607 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G14760 | AT2G14760 |
| AGL87 | 0.139175318 | 0.033099943 | 0.106075375 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G22590 | AGL87 |
| AT2G17600 | 0.105079547 | 0.000000000 | 0.105079547 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G17600 | AT2G17600 |
| ASG3 | 0.153960813 | 0.018656716 | 0.103988574 | 0.000000000 | 0.002868069 | 0.002982303 | 0.02546515 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G44980 | ASG3 |
| AT1G02040 | 0.057532915 | 0.000000000 | 0.057532915 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G02040 | AT1G02040 |
| BPC5 | 0.067838909 | 0.013239977 | 0.054598932 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G38910 | BPC5 |
| SUVH2 | 0.088595628 | 0.000000000 | 0.048157148 | 0.000000000 | 0.002868069 | 0.002982303 | 0.02574518 | 0.000000000 | 0.008842931 | 0.000000000 | 0.000000000 | AT2G33290 | SUVH2 |
| NAC005 | 0.032032046 | 0.000000000 | 0.032032046 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G02250 | NAC005 |
| IAA34 | 0.024804739 | 0.000000000 | 0.024804739 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G15050 | IAA34 |
| CIA2 | 0.038534594 | 0.010153558 | 0.024556945 | 0.000000000 | 0.003824092 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G57180 | CIA2 |
| AT2G24680 | 0.029624829 | 0.000000000 | 0.016915098 | 0.000000000 | 0.000000000 | 0.000000000 | 0.01270973 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G24680 | AT2G24680 |
| RR14 | 0.029976546 | 0.000000000 | 0.015544609 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.014431937 | AT2G01760 | RR14 |
| AT2G28920 | 0.012650573 | 0.000000000 | 0.012650573 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G28920 | AT2G28920 |
| MYB97 | 0.009373312 | 0.000000000 | 0.009373312 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G26930 | MYB97 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(tri_rank[1:10,], aes(x=reorder(GeneName, tri, decreasing = FALSE), y=tri)) + geom_point(size=4)+
labs(title="Trichoblast-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(tri_rank,"Trichoblast_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
## Top20 only
tf_rank <- tri_rank %>% rownames(.)
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Trichoblast ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
q1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3])
q2 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3])
q3 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3])
q1 <- grid.grabExpr(draw(q1))
q2 <- grid.grabExpr(draw(q2))
q3 <- grid.grabExpr(draw(q3))
options(repr.plot.width=6, repr.plot.height=8)
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q1,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q2,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q3,nrow=2,rel_heights = c(1, 8)),nrow=3)
cor_rank <- bc_rank[which(bc_rank$cor*2 > bc_rank$all),]%>% arrange(desc(cor))
cor_rank$GeneName <- rownames(cor_rank)
cor_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| AT1G05710 | 7.83989003 | 0.07228446 | 0.000000000 | 5.77386624 | 1.973841857 | 0.01444529 | 0.005452182 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G05710 | AT1G05710 |
| AT1G62975 | 6.72777431 | 1.13322162 | 0.146830936 | 3.40415652 | 1.322609983 | 0.27190233 | 0.136499115 | 0.1189206 | 0.193633211 | 0.000000000 | 0.000000000 | AT1G62975 | AT1G62975 |
| AT1G72210 | 4.37996569 | 0.00000000 | 0.000000000 | 3.26158461 | 0.916443668 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.201937410 | AT1G72210 | AT1G72210 |
| AT2G38300 | 3.02146138 | 0.00000000 | 0.000000000 | 2.35652364 | 0.308759503 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.356178233 | AT2G38300 | AT2G38300 |
| LAF1 | 2.65672644 | 0.07291432 | 0.000000000 | 2.16594894 | 0.417863168 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G25560 | LAF1 |
| MYB86 | 3.66808131 | 1.58670619 | 0.035736296 | 1.89230824 | 0.006692161 | 0.00000000 | 0.000000000 | 0.1034472 | 0.004497468 | 0.028711865 | 0.009981880 | AT5G26660 | MYB86 |
| JAZ6 | 2.58639791 | 0.32191094 | 0.079950398 | 1.76647996 | 0.194759488 | 0.10574310 | 0.065125186 | 0.0000000 | 0.019982403 | 0.008591619 | 0.023854811 | AT1G72450 | JAZ6 |
| AT2G42660 | 1.45982831 | 0.05077908 | 0.000000000 | 1.29597136 | 0.000000000 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.113077867 | AT2G42660 | AT2G42660 |
| IDD4 | 1.73576688 | 0.00000000 | 0.000000000 | 1.28051964 | 0.455247239 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G02080 | IDD4 |
| LRP1 | 2.28649090 | 0.00000000 | 0.000000000 | 1.24876279 | 0.251133632 | 0.27895655 | 0.482865086 | 0.0000000 | 0.012253259 | 0.000000000 | 0.012519592 | AT5G12330 | LRP1 |
| AT4G28030 | 2.08413938 | 0.28480728 | 0.443496572 | 1.06622232 | 0.257186184 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.032427031 | AT4G28030 | AT4G28030 |
| AT1G64380 | 1.91747634 | 0.59839625 | 0.042775041 | 1.04414078 | 0.232164269 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G64380 | AT1G64380 |
| RVN | 1.63173317 | 0.00000000 | 0.000000000 | 0.84336498 | 0.782052065 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.006316118 | AT2G02070 | RVN |
| GLK2 | 0.94299487 | 0.00000000 | 0.000000000 | 0.58189615 | 0.002868069 | 0.11657498 | 0.190199334 | 0.0000000 | 0.047677935 | 0.000000000 | 0.003778406 | AT5G44190 | GLK2 |
| AT2G46810 | 0.20185238 | 0.00000000 | 0.003992795 | 0.11957719 | 0.041082783 | 0.00000000 | 0.011148486 | 0.0000000 | 0.000000000 | 0.000000000 | 0.026051124 | AT2G46810 | AT2G46810 |
| AT3G18960 | 0.09413402 | 0.00000000 | 0.000000000 | 0.08787423 | 0.000000000 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.006259796 | AT3G18960 | AT3G18960 |
| AT4G11400 | 0.03603606 | 0.00000000 | 0.000000000 | 0.02425674 | 0.009053224 | 0.00000000 | 0.002726091 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G11400 | AT4G11400 |
| PIL5 | 0.03518538 | 0.00000000 | 0.000000000 | 0.02084504 | 0.014340344 | 0.00000000 | 0.000000000 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G20180 | PIL5 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(cor_rank[1:10,], aes(x=reorder(GeneName, cor, decreasing = FALSE), y=cor)) + geom_point(size=4)+
labs(title="Cortex-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(cor_rank,"Cortex_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- cor_rank %>% rownames(.)
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
#p4 <- plot_bc(tf_rank[16]) + plot_blank("Empty")+ plot_blank("Empty") + plot_blank("Empty")+ plot_blank("Empty")
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
#p8 <- plot_oc(tf_rank[16]) + plot_blank("Empty")+ plot_blank("Empty") + plot_blank("Empty")+ plot_blank("Empty")
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
#p12 <- plot_ic(tf_rank[16]) + plot_blank("Empty")+ plot_blank("Empty") + plot_blank("Empty")+ plot_blank("Empty")
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
#p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
#p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
#p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=9)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Cortex ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,nrow=3),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,nrow=3),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,nrow=3),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
## Top 10 only
tf_rank <- cor_rank %>% rownames(.)
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
#p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
#p4 <- plot_bc(tf_rank[16]) + plot_blank("Empty")+ plot_blank("Empty") + plot_blank("Empty")+ plot_blank("Empty")
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
#p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
#p8 <- plot_oc(tf_rank[16]) + plot_blank("Empty")+ plot_blank("Empty") + plot_blank("Empty")+ plot_blank("Empty")
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
#p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
#p12 <- plot_ic(tf_rank[16]) + plot_blank("Empty")+ plot_blank("Empty") + plot_blank("Empty")+ plot_blank("Empty")
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
#p3 <- grid.grabExpr(draw(p3))
#p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
#p7 <- grid.grabExpr(draw(p7))
#p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
#p11 <- grid.grabExpr(draw(p11))
#p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=5)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Cortex ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,nrow=2),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,nrow=2),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,nrow=2),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
q1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3])
q2 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3])
q3 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3])
q1 <- grid.grabExpr(draw(q1))
q2 <- grid.grabExpr(draw(q2))
q3 <- grid.grabExpr(draw(q3))
options(repr.plot.width=6, repr.plot.height=8)
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q1,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q2,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q3,nrow=2,rel_heights = c(1, 8)),nrow=3)
end_rank <- bc_rank[which(bc_rank$end*2 > bc_rank$all),]%>% arrange(desc(end))
end_rank$GeneName <- rownames(end_rank)
end_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| MYB36 | 20.574179871 | 0.000000000 | 0.000000000 | 6.290936886 | 10.748544272 | 3.534698713 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G57620 | MYB36 |
| MYB74 | 12.716442815 | 0.000000000 | 0.000000000 | 4.532213333 | 7.685381936 | 0.236172960 | 0.012475395 | 0.182513773 | 0.000000000 | 0.014864734 | 0.052820684 | AT4G05100 | MYB74 |
| MYB68 | 9.699006069 | 0.000000000 | 0.000000000 | 2.501400511 | 6.179638016 | 1.017967543 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G65790 | MYB68 |
| SOM | 7.741216041 | 0.050269055 | 0.000000000 | 2.027707378 | 4.021560442 | 1.244198607 | 0.345040865 | 0.000000000 | 0.052439694 | 0.000000000 | 0.000000000 | AT1G03790 | SOM |
| BLJ | 4.557129505 | 0.000000000 | 0.000000000 | 0.643910731 | 3.719412679 | 0.193806095 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G14580 | BLJ |
| RAX2 | 5.318435677 | 0.147471024 | 0.049460104 | 1.185754593 | 3.465686223 | 0.450624550 | 0.019439183 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G36890 | RAX2 |
| SCR | 4.753144752 | 0.000000000 | 0.000000000 | 1.662358141 | 3.003742831 | 0.087043779 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G54220 | SCR |
| TLP11 | 4.155878032 | 0.006012685 | 0.370838723 | 0.278142330 | 2.179886146 | 0.627860320 | 0.505965671 | 0.000000000 | 0.187172158 | 0.000000000 | 0.000000000 | AT5G18680 | TLP11 |
| SCL3 | 3.322564901 | 0.000000000 | 0.000000000 | 0.687705471 | 1.761112367 | 0.234680845 | 0.112334395 | 0.000000000 | 0.000000000 | 0.128682075 | 0.398049747 | AT1G50420 | SCL3 |
| chr31 | 1.702067100 | 0.000000000 | 0.000000000 | 0.000000000 | 1.572727090 | 0.092754632 | 0.000000000 | 0.012541359 | 0.024044019 | 0.000000000 | 0.000000000 | AT1G05490 | chr31 |
| BIB | 1.406028193 | 0.000000000 | 0.000000000 | 0.010856804 | 1.395171389 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G45260 | BIB |
| bZIP58 | 1.661611692 | 0.000000000 | 0.000000000 | 0.227490055 | 1.306590616 | 0.018751076 | 0.108779944 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G13600 | bZIP58 |
| MYB122 | 1.962060042 | 0.000000000 | 0.000000000 | 0.666940898 | 1.208371730 | 0.063664777 | 0.023082637 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G74080 | MYB122 |
| AGL42 | 1.244914177 | 0.000000000 | 0.000000000 | 0.446109295 | 0.726597205 | 0.042963128 | 0.029244549 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G62165 | AGL42 |
| ERF15 | 1.314549626 | 0.000000000 | 0.000000000 | 0.590902307 | 0.704993808 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.018653511 | AT2G31230 | ERF15 |
| AGL102 | 0.685543758 | 0.000000000 | 0.000000000 | 0.024906311 | 0.644352188 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.016285259 | AT1G47760 | AGL102 |
| AT4G38340 | 0.442251375 | 0.000000000 | 0.000000000 | 0.014497423 | 0.427753952 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G38340 | AT4G38340 |
| SIGA | 0.430563439 | 0.000000000 | 0.000000000 | 0.030488331 | 0.301306106 | 0.059055838 | 0.035934757 | 0.000000000 | 0.000000000 | 0.000000000 | 0.003778406 | AT1G64860 | SIGA |
| AT2G43140 | 0.335394776 | 0.000000000 | 0.000000000 | 0.066194151 | 0.269200625 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G43140 | AT2G43140 |
| TIFY8 | 0.439795518 | 0.000000000 | 0.000000000 | 0.011583012 | 0.253202346 | 0.045342907 | 0.000000000 | 0.000000000 | 0.034522976 | 0.056150682 | 0.038993595 | AT4G32570 | TIFY8 |
| AT5G26749 | 0.384931821 | 0.076016044 | 0.030910265 | 0.003880024 | 0.230091801 | 0.028597865 | 0.015435821 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G26749 | AT5G26749 |
| FAR1 | 0.361206182 | 0.000000000 | 0.003293898 | 0.036799976 | 0.189857545 | 0.025975440 | 0.057755511 | 0.000000000 | 0.040380886 | 0.007142926 | 0.000000000 | AT4G15090 | FAR1 |
| ULT2 | 0.355119532 | 0.176242108 | 0.000000000 | 0.000000000 | 0.178877425 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G20825 | ULT2 |
| AT2G33720 | 0.157034612 | 0.000000000 | 0.000000000 | 0.004145189 | 0.152889423 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G33720 | AT2G33720 |
| AMS | 0.129131872 | 0.000000000 | 0.000000000 | 0.006228522 | 0.122903350 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G16910 | AMS |
| NF-YA2 | 0.188031899 | 0.000000000 | 0.000000000 | 0.006204071 | 0.107483285 | 0.004237288 | 0.070107255 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G05690 | NF-YA2 |
| ERF73 | 0.142871090 | 0.000000000 | 0.000000000 | 0.000000000 | 0.096760814 | 0.007544386 | 0.005302323 | 0.000000000 | 0.000000000 | 0.022000456 | 0.011263112 | AT1G72360 | ERF73 |
| AT1G18335 | 0.184235887 | 0.011770842 | 0.030612477 | 0.000000000 | 0.094516912 | 0.014560717 | 0.007418725 | 0.006287192 | 0.019069022 | 0.000000000 | 0.000000000 | AT1G18335 | AT1G18335 |
| AT4G00390 | 0.072093134 | 0.000000000 | 0.000000000 | 0.000000000 | 0.072093134 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G00390 | AT4G00390 |
| AT3G18870 | 0.079208553 | 0.000000000 | 0.000000000 | 0.010395189 | 0.062316358 | 0.000000000 | 0.000000000 | 0.000000000 | 0.006497006 | 0.000000000 | 0.000000000 | AT3G18870 | AT3G18870 |
| AT1G76880 | 0.066020974 | 0.000000000 | 0.000000000 | 0.000000000 | 0.061949340 | 0.000000000 | 0.000000000 | 0.000000000 | 0.004071634 | 0.000000000 | 0.000000000 | AT1G76880 | AT1G76880 |
| HB28 | 0.089080723 | 0.011770842 | 0.009373312 | 0.012041042 | 0.055895527 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G50890 | HB28 |
| NF-YA6 | 0.051314786 | 0.000000000 | 0.000000000 | 0.000000000 | 0.041779659 | 0.000000000 | 0.009535127 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G14020 | NF-YA6 |
| 4-Sep | 0.061140978 | 0.000000000 | 0.020499200 | 0.000000000 | 0.040641778 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G03710 | 4-Sep |
| FD | 0.052058744 | 0.000000000 | 0.000000000 | 0.010984046 | 0.031031246 | 0.000000000 | 0.000000000 | 0.000000000 | 0.010043451 | 0.000000000 | 0.000000000 | AT4G35900 | FD |
| AT3G07500 | 0.054236833 | 0.000000000 | 0.000000000 | 0.000000000 | 0.028488413 | 0.025748421 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G07500 | AT3G07500 |
| AGL67 | 0.023112209 | 0.000000000 | 0.000000000 | 0.000000000 | 0.023112209 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G77950 | AGL67 |
| AT1G61970 | 0.039740148 | 0.000000000 | 0.000000000 | 0.000000000 | 0.022206610 | 0.000000000 | 0.006785515 | 0.000000000 | 0.000000000 | 0.000000000 | 0.010748023 | AT1G61970 | AT1G61970 |
| DUO1 | 0.014699561 | 0.000000000 | 0.000000000 | 0.000000000 | 0.009187955 | 0.000000000 | 0.005511606 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G60460 | DUO1 |
| AGL13 | 0.010731926 | 0.000000000 | 0.000000000 | 0.000000000 | 0.008604207 | 0.000000000 | 0.002127720 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G61120 | AGL13 |
| AGL62 | 0.007648184 | 0.000000000 | 0.000000000 | 0.000000000 | 0.007648184 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G60440 | AGL62 |
| TDF1 | 0.006692161 | 0.000000000 | 0.000000000 | 0.000000000 | 0.006692161 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G28470 | TDF1 |
options(repr.plot.width=8, repr.plot.height=4)
ggplot(end_rank[1:10,], aes(x=reorder(GeneName, end, decreasing = FALSE), y=end)) + geom_point(size=4)+
labs(title="Endodermis-specific TF Prioritization",x="", y = "Combined centrality score (betweeness, out and in degree)")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(end_rank,"Endodermis_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- end_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Endodermis ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
tf_rank <- end_rank %>% rownames(.)
# Max 10
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
#p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
#p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
#p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
#p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
#p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
#p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
#p3 <- grid.grabExpr(draw(p3))
#p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
#p7 <- grid.grabExpr(draw(p7))
#p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
#p11 <- grid.grabExpr(draw(p11))
#p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=5)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Endodermis ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,nrow=2),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,nrow=2),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,nrow=2),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
q1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5]) + plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
q2 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5]) + plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
q3 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5]) + plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
q1 <- grid.grabExpr(draw(q1))
q2 <- grid.grabExpr(draw(q2))
q3 <- grid.grabExpr(draw(q3))
options(repr.plot.width=16, repr.plot.height=8)
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q1,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q2,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q3,nrow=2,rel_heights = c(1, 8)),nrow=3)
per_rank <- bc_rank[which(bc_rank$per*2 > bc_rank$all),]%>% arrange(desc(per))
per_rank$GeneName <- rownames(per_rank)
per_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| MYBC1 | 14.91041315 | 0.00000000 | 0.00000000 | 0.65860261 | 2.435376723 | 8.72219752 | 2.90627762 | 0.000000000 | 0.187958672 | 0.00000000 | 0 | AT2G40970 | MYBC1 |
| AT4G29100 | 15.42626741 | 0.00000000 | 0.00000000 | 0.04247104 | 0.180997736 | 7.75003971 | 5.13998592 | 0.000000000 | 2.312773002 | 0.00000000 | 0 | AT4G29100 | AT4G29100 |
| NUC | 6.13113863 | 0.00000000 | 0.00000000 | 0.41835765 | 0.098575284 | 4.34553862 | 1.04180510 | 0.000000000 | 0.226861976 | 0.00000000 | 0 | AT5G44160 | NUC |
| MGP | 4.89894588 | 0.25223575 | 0.00000000 | 0.20479261 | 0.109763013 | 3.69040420 | 0.63394150 | 0.000000000 | 0.007808814 | 0.00000000 | 0 | AT1G03840 | MGP |
| AT3G21330 | 4.37929863 | 0.16406137 | 0.00000000 | 0.09196824 | 0.153719057 | 3.39359729 | 0.57595268 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT3G21330 | AT3G21330 |
| LBD14 | 4.27221824 | 0.00000000 | 0.00000000 | 0.01623535 | 0.051884948 | 3.37129302 | 0.83280492 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT2G31310 | LBD14 |
| IDD11 | 4.79842980 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 3.20404576 | 1.59438404 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT3G13810 | IDD11 |
| AT2G20100 | 4.29588276 | 0.00000000 | 0.00000000 | 0.00000000 | 0.032630438 | 2.82049079 | 1.26913958 | 0.173621948 | 0.000000000 | 0.00000000 | 0 | AT2G20100 | AT2G20100 |
| GATA23 | 3.85660749 | 0.00000000 | 0.00000000 | 0.00000000 | 0.007874926 | 2.67696633 | 1.17176623 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT5G26930 | GATA23 |
| AT2G14880 | 4.16782313 | 0.43577425 | 0.04114576 | 0.35557855 | 0.287664612 | 2.26879846 | 0.77886149 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT2G14880 | AT2G14880 |
| SAP | 2.74523806 | 0.12877896 | 0.00000000 | 0.25676267 | 0.093279496 | 2.14462678 | 0.12179016 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT5G35770 | SAP |
| LAS | 0.51091872 | 0.00000000 | 0.00000000 | 0.00000000 | 0.053461698 | 0.33109447 | 0.12636255 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT1G55580 | LAS |
| DEL1 | 0.43576435 | 0.04833297 | 0.03480252 | 0.02158295 | 0.019448661 | 0.23401830 | 0.00000000 | 0.002508272 | 0.037835401 | 0.03723528 | 0 | AT3G48160 | DEL1 |
| BOP2 | 0.34399626 | 0.00000000 | 0.00000000 | 0.00000000 | 0.003074926 | 0.20966660 | 0.13125473 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT2G41370 | BOP2 |
| AT1G78930 | 0.12300974 | 0.00000000 | 0.00000000 | 0.00000000 | 0.002868069 | 0.08547529 | 0.03466638 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT1G78930 | AT1G78930 |
| AT4G31060 | 0.14188633 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.07268985 | 0.01588433 | 0.000000000 | 0.025452986 | 0.02785916 | 0 | AT4G31060 | AT4G31060 |
| WOX14 | 0.10054729 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.05461600 | 0.04342302 | 0.002508272 | 0.000000000 | 0.00000000 | 0 | AT1G20700 | WOX14 |
| AT3G61550 | 0.04333459 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.04333459 | 0.00000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT3G61550 | AT3G61550 |
| PRR3 | 0.02667455 | 0.00000000 | 0.00000000 | 0.00000000 | 0.000000000 | 0.02667455 | 0.00000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0 | AT5G60100 | PRR3 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(per_rank[1:10,], aes(x=reorder(GeneName, per, decreasing = FALSE), y=per)) + geom_point(size=4)+
labs(title="Pericycle-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(per_rank,"Pericycle_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- per_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Pericycle ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
q1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3])
q2 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3])
q3 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3])
q1 <- grid.grabExpr(draw(q1))
q2 <- grid.grabExpr(draw(q2))
q3 <- grid.grabExpr(draw(q3))
options(repr.plot.width=6, repr.plot.height=8)
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q1,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q2,nrow=2,rel_heights = c(1, 8))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),q3,nrow=2,rel_heights = c(1, 8)),nrow=3)
pro_rank <- bc_rank[which(bc_rank$pro*2 > bc_rank$all),]%>% arrange(desc(pro))
pro_rank$GeneName <- rownames(pro_rank)
pro_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| MYB43 | 16.063077043 | 0.00000000 | 0.000000000 | 0.00000000 | 0.018462790 | 4.879714006 | 8.047714481 | 0.240494235 | 2.876691531 | 0.000000000 | 0.000000000 | AT5G16600 | MYB43 |
| ABO3 | 12.418181467 | 0.38711177 | 0.072070692 | 0.00000000 | 0.067673475 | 4.010305263 | 7.290287611 | 0.174468836 | 0.416263819 | 0.000000000 | 0.000000000 | AT1G66600 | ABO3 |
| TCP15 | 9.177076070 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.649598318 | 4.681848534 | 2.137878696 | 1.707750521 | 0.000000000 | 0.000000000 | AT1G69690 | TCP15 |
| HAT9 | 5.492151241 | 0.06870023 | 0.000000000 | 0.01447595 | 0.013073992 | 1.585263738 | 3.699553013 | 0.000000000 | 0.111084324 | 0.000000000 | 0.000000000 | AT2G22800 | HAT9 |
| NAC001 | 5.586097156 | 0.00000000 | 0.004202144 | 0.48247334 | 0.179606108 | 1.415983701 | 2.859578995 | 0.006254167 | 0.637998702 | 0.000000000 | 0.000000000 | AT1G01010 | NAC001 |
| ERF12 | 4.871129058 | 0.00000000 | 0.000000000 | 0.00000000 | 0.012143626 | 1.683704940 | 2.816567231 | 0.000000000 | 0.358713261 | 0.000000000 | 0.000000000 | AT1G28360 | ERF12 |
| IDD14 | 5.343304900 | 0.00000000 | 0.000000000 | 0.01079147 | 0.003872669 | 1.393400783 | 2.734130023 | 0.391099760 | 0.810010191 | 0.000000000 | 0.000000000 | AT1G68130 | IDD14 |
| AT1G75490 | 2.958317094 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.170210951 | 2.465071484 | 0.000000000 | 0.310691582 | 0.000000000 | 0.012343077 | AT1G75490 | AT1G75490 |
| AT4G20970 | 2.161550767 | 0.00000000 | 0.000000000 | 0.00000000 | 0.002868069 | 0.427155755 | 1.678458718 | 0.000000000 | 0.053068226 | 0.000000000 | 0.000000000 | AT4G20970 | AT4G20970 |
| AT2G40200 | 2.380382330 | 0.00000000 | 0.012278472 | 0.00000000 | 0.000000000 | 0.371988922 | 1.675323042 | 0.000000000 | 0.320791894 | 0.000000000 | 0.000000000 | AT2G40200 | AT2G40200 |
| SHY2 | 2.164073331 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.250035517 | 1.427622721 | 0.181634565 | 0.304780528 | 0.000000000 | 0.000000000 | AT1G04240 | SHY2 |
| AT4G25410 | 2.132630161 | 0.05040275 | 0.049127548 | 0.00000000 | 0.032204709 | 0.315071899 | 1.322093151 | 0.055658640 | 0.308071466 | 0.000000000 | 0.000000000 | AT4G25410 | AT4G25410 |
| NAC080 | 1.824714942 | 0.00000000 | 0.000000000 | 0.00000000 | 0.010723110 | 0.289794777 | 1.304852705 | 0.000000000 | 0.189405441 | 0.024611422 | 0.005327487 | AT5G07680 | NAC080 |
| NAC045 | 1.652836169 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.136672103 | 0.867559280 | 0.040550450 | 0.608054336 | 0.000000000 | 0.000000000 | AT3G03200 | NAC045 |
| HB18 | 1.179598985 | 0.00000000 | 0.000000000 | 0.00000000 | 0.006692161 | 0.258665767 | 0.753756147 | 0.029984702 | 0.130500209 | 0.000000000 | 0.000000000 | AT1G70920 | HB18 |
| ARF19 | 1.032683225 | 0.01713678 | 0.064638504 | 0.03561580 | 0.036868764 | 0.167644718 | 0.575714484 | 0.013745958 | 0.067300926 | 0.000000000 | 0.054017294 | AT1G19220 | ARF19 |
| LBD29 | 0.594929037 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.057825252 | 0.537103785 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G58190 | LBD29 |
| STH | 0.716741910 | 0.00000000 | 0.000000000 | 0.02066151 | 0.008604207 | 0.102889289 | 0.358427175 | 0.021816819 | 0.050331909 | 0.066920121 | 0.087090879 | AT2G31380 | STH |
| AT1G24210 | 0.197216762 | 0.00000000 | 0.000000000 | 0.00000000 | 0.006692161 | 0.065776052 | 0.124748549 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G24210 | AT1G24210 |
| AT4G27240 | 0.162221139 | 0.00000000 | 0.000000000 | 0.02158295 | 0.009053224 | 0.030583695 | 0.095433302 | 0.000000000 | 0.005567970 | 0.000000000 | 0.000000000 | AT4G27240 | AT4G27240 |
| DAR6 | 0.103486477 | 0.00776833 | 0.000000000 | 0.00000000 | 0.003824092 | 0.000000000 | 0.091894056 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G66620 | DAR6 |
| WRKY67 | 0.158987824 | 0.00000000 | 0.000000000 | 0.00000000 | 0.002868069 | 0.075702136 | 0.080417619 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G66550 | WRKY67 |
| AT5G55580 | 0.123376860 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.041387259 | 0.074846675 | 0.000000000 | 0.000000000 | 0.007142926 | 0.000000000 | AT5G55580 | AT5G55580 |
| AT1G74120 | 0.057441290 | 0.00000000 | 0.000000000 | 0.00000000 | 0.009560229 | 0.000000000 | 0.033422822 | 0.000000000 | 0.014458239 | 0.000000000 | 0.000000000 | AT1G74120 | AT1G74120 |
| EMB3114 | 0.022625319 | 0.00000000 | 0.000000000 | 0.00000000 | 0.003824092 | 0.006091497 | 0.012709730 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G36000 | EMB3114 |
| NF-YA8 | 0.018139334 | 0.00000000 | 0.000000000 | 0.00000000 | 0.008604207 | 0.000000000 | 0.009535127 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G17590 | NF-YA8 |
| HB51 | 0.008649420 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.008649420 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G03790 | HB51 |
| IAA32 | 0.010764473 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.007418725 | 0.000000000 | 0.003345748 | 0.000000000 | 0.000000000 | AT2G01200 | IAA32 |
| MYB95 | 0.005860963 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.005860963 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G74430 | MYB95 |
| AT1G18960 | 0.003733243 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.003733243 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT1G18960 | AT1G18960 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(pro_rank[1:10,], aes(x=reorder(GeneName, pro, decreasing = FALSE), y=pro)) + geom_point(size=4)+
labs(title="Procambium-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(pro_rank,"Procambium_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- pro_rank %>% rownames(.)
# Max 30
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_blank(tf_rank[15])
p4 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p5 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p6 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_blank(tf_rank[15])
p7 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p8 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p9 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_blank(tf_rank[15])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=10)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Procambium ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,nrow=3),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p4,p5,p6,nrow=3),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p7,p8,p9,nrow=3),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
phl_rank <- bc_rank[which(bc_rank$phl*2 > bc_rank$all),]%>% arrange(desc(phl))
phl_rank$GeneName <- rownames(phl_rank)
phl_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| APL | 17.844322073 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.895694774 | 1.714937260 | 2.164953147 | 12.068736892 | 0.000000000 | 0.000000000 | AT1G79430 | APL |
| OBP2 | 19.626516178 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 2.886506004 | 5.836194997 | 0.015082655 | 10.888732521 | 0.000000000 | 0.000000000 | AT1G07640 | OBP2 |
| AT3G12730 | 9.807026857 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.085095947 | 0.202927880 | 0.000000000 | 8.519003030 | 0.000000000 | 0.000000000 | AT3G12730 | AT3G12730 |
| DOF6 | 10.369908100 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.293766765 | 0.462508272 | 1.782009903 | 6.831623160 | 0.000000000 | 0.000000000 | AT3G45610 | DOF6 |
| AT2G03500 | 8.337749613 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.110191244 | 1.136420947 | 0.020165247 | 6.070972175 | 0.000000000 | 0.000000000 | AT2G03500 | AT2G03500 |
| DAR2 | 8.618352004 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.143452224 | 1.108834134 | 0.468422625 | 5.897643021 | 0.000000000 | 0.000000000 | AT2G39830 | DAR2 |
| AT2G28810 | 9.426614047 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.580162327 | 2.663112048 | 0.026254293 | 5.157085378 | 0.000000000 | 0.000000000 | AT2G28810 | AT2G28810 |
| HCA2 | 5.517875746 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.348325274 | 0.231431791 | 0.015214752 | 4.922903929 | 0.000000000 | 0.000000000 | AT5G62940 | HCA2 |
| NAC057 | 5.520438511 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.345280579 | 0.512603280 | 0.015214752 | 4.647339899 | 0.000000000 | 0.000000000 | AT3G17730 | NAC057 |
| AT5G41380 | 4.485095958 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.105076026 | 0.019805580 | 0.000000000 | 4.360214352 | 0.000000000 | 0.000000000 | AT5G41380 | AT5G41380 |
| AT4G37180 | 5.223395955 | 0.00793207 | 0.007472171 | 0.005836971 | 0.048259729 | 0.649975317 | 0.323930557 | 0.017623951 | 3.967073511 | 0.084287560 | 0.111004117 | AT4G37180 | AT4G37180 |
| NAC020 | 4.474851299 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.686697179 | 0.328105413 | 0.013878056 | 3.446170651 | 0.000000000 | 0.000000000 | AT1G54330 | NAC020 |
| NAC2 | 3.496258409 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.308778632 | 0.425776168 | 0.000000000 | 2.761703609 | 0.000000000 | 0.000000000 | AT3G15510 | NAC2 |
| bZIP19 | 4.262023240 | 0.14100327 | 0.014058465 | 0.030897113 | 0.076054930 | 0.450617496 | 0.823885719 | 0.016320279 | 2.709185973 | 0.000000000 | 0.000000000 | AT4G35040 | bZIP19 |
| HB21 | 4.459722485 | 0.00000000 | 0.000000000 | 0.000000000 | 0.025413486 | 0.482174192 | 1.358219706 | 0.000000000 | 2.593915101 | 0.000000000 | 0.000000000 | AT2G18550 | HB21 |
| AT1G49560 | 4.767954053 | 0.32088670 | 0.008864929 | 0.424452385 | 0.399695412 | 0.230026185 | 0.135960540 | 0.030264383 | 2.448177777 | 0.294146744 | 0.475478996 | AT1G49560 | AT1G49560 |
| REM22 | 2.822338450 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.198746448 | 0.225280767 | 0.006221143 | 2.392090092 | 0.000000000 | 0.000000000 | AT3G17010 | REM22 |
| FLP | 4.235152604 | 0.56810859 | 0.031657435 | 0.107744382 | 0.117251965 | 0.175675640 | 0.225020013 | 0.016353303 | 2.270932524 | 0.506727685 | 0.215681071 | AT1G14350 | FLP |
| AT1G63820 | 3.720006790 | 0.00000000 | 0.000000000 | 0.000000000 | 0.009329967 | 0.848743347 | 0.782290821 | 0.000000000 | 2.079642654 | 0.000000000 | 0.000000000 | AT1G63820 | AT1G63820 |
| AT1G26790 | 2.910254699 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.179393715 | 0.660556980 | 0.000000000 | 2.070304004 | 0.000000000 | 0.000000000 | AT1G26790 | AT1G26790 |
| CRF1 | 3.720408554 | 0.21276123 | 0.206976144 | 0.261873284 | 0.324733096 | 0.308264664 | 0.138417643 | 0.000000000 | 1.993441722 | 0.195940122 | 0.078000645 | AT4G11140 | CRF1 |
| AT5G02460 | 3.055381286 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.565451317 | 0.519269935 | 0.013812007 | 1.956848028 | 0.000000000 | 0.000000000 | AT5G02460 | AT5G02460 |
| AT5G63700 | 3.220104522 | 0.00000000 | 0.000000000 | 0.556733035 | 0.000000000 | 0.044349903 | 0.029599282 | 0.000000000 | 1.795400156 | 0.000000000 | 0.794022145 | AT5G63700 | AT5G63700 |
| NAC086 | 1.671278410 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.058164212 | 0.000000000 | 0.000000000 | 1.613114198 | 0.000000000 | 0.000000000 | AT5G17260 | NAC086 |
| WRKY32 | 2.765045412 | 0.00000000 | 0.000000000 | 0.000000000 | 0.070488176 | 0.566141217 | 0.478017862 | 0.007524815 | 1.558337999 | 0.059820797 | 0.024714547 | AT4G30935 | WRKY32 |
| VOZ1 | 2.699988128 | 0.00000000 | 0.000000000 | 0.000000000 | 0.044628126 | 0.473464461 | 0.621765050 | 0.083750499 | 1.404101573 | 0.033869726 | 0.038408694 | AT1G28520 | VOZ1 |
| MYB10 | 2.103618150 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.035372330 | 0.498233312 | 0.247741073 | 1.322271434 | 0.000000000 | 0.000000000 | AT3G12820 | MYB10 |
| GATA20 | 1.684610713 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.277759093 | 0.092264430 | 0.000000000 | 1.314587190 | 0.000000000 | 0.000000000 | AT2G18380 | GATA20 |
| SVP | 1.432290958 | 0.00000000 | 0.000000000 | 0.029604337 | 0.034589965 | 0.094637812 | 0.030758331 | 0.000000000 | 1.213039110 | 0.000000000 | 0.029661402 | AT2G22540 | SVP |
| AGL15 | 1.098345251 | 0.00000000 | 0.000000000 | 0.000000000 | 0.006692161 | 0.050236157 | 0.043390946 | 0.010132160 | 0.987893828 | 0.000000000 | 0.000000000 | AT5G13790 | AGL15 |
| KNAT2 | 1.461220827 | 0.00000000 | 0.000000000 | 0.018909150 | 0.168804306 | 0.226054236 | 0.066045262 | 0.000000000 | 0.981407873 | 0.000000000 | 0.000000000 | AT1G70510 | KNAT2 |
| ET2 | 0.852503850 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.068770232 | 0.078536301 | 0.000000000 | 0.705197317 | 0.000000000 | 0.000000000 | AT5G56780 | ET2 |
| AT1G64530 | 1.120045796 | 0.03882994 | 0.069895732 | 0.108418064 | 0.095720622 | 0.050855970 | 0.036356583 | 0.006320216 | 0.635192817 | 0.014544308 | 0.063911545 | AT1G64530 | AT1G64530 |
| WOX2 | 0.275019516 | 0.00000000 | 0.000000000 | 0.000000000 | 0.032162538 | 0.000000000 | 0.000000000 | 0.000000000 | 0.242856978 | 0.000000000 | 0.000000000 | AT5G59340 | WOX2 |
| AT1G02030 | 0.314641406 | 0.00000000 | 0.004686656 | 0.000000000 | 0.031876961 | 0.000000000 | 0.000000000 | 0.000000000 | 0.225122356 | 0.052955432 | 0.000000000 | AT1G02030 | AT1G02030 |
| AT1G58220 | 0.339257487 | 0.00000000 | 0.006587797 | 0.000000000 | 0.028488413 | 0.000000000 | 0.028425231 | 0.017623951 | 0.200343122 | 0.012091053 | 0.045697921 | AT1G58220 | AT1G58220 |
| AGL80 | 0.265282542 | 0.00000000 | 0.000000000 | 0.000000000 | 0.002868069 | 0.004315187 | 0.059445379 | 0.000000000 | 0.198653907 | 0.000000000 | 0.000000000 | AT5G48670 | AGL80 |
| AT3G06220 | 0.180725116 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.180725116 | 0.000000000 | 0.000000000 | AT3G06220 | AT3G06220 |
| PIF7 | 0.270023952 | 0.00000000 | 0.023133864 | 0.092271047 | 0.001912046 | 0.000000000 | 0.000000000 | 0.000000000 | 0.152706995 | 0.000000000 | 0.000000000 | AT5G61270 | PIF7 |
| SPL10 | 0.193594293 | 0.00000000 | 0.004202144 | 0.000000000 | 0.004780115 | 0.000000000 | 0.024395674 | 0.000000000 | 0.145557421 | 0.006118379 | 0.008540560 | AT1G27370 | SPL10 |
| SPL13A | 0.181543092 | 0.00000000 | 0.005195039 | 0.000000000 | 0.000000000 | 0.000000000 | 0.005454413 | 0.000000000 | 0.127166742 | 0.032245373 | 0.011481524 | AT5G50570 | SPL13A |
| AT5G63080 | 0.198822428 | 0.00000000 | 0.003293898 | 0.000000000 | 0.008604207 | 0.012215950 | 0.015995872 | 0.000000000 | 0.101449741 | 0.039772184 | 0.017490575 | AT5G63080 | AT5G63080 |
| AT3G46070 | 0.106851330 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.071187905 | 0.035663425 | 0.000000000 | AT3G46070 | AT3G46070 |
| DRD1 | 0.112080387 | 0.00000000 | 0.000000000 | 0.000000000 | 0.003824092 | 0.021170077 | 0.010144816 | 0.000000000 | 0.061376222 | 0.000000000 | 0.015565179 | AT2G16390 | DRD1 |
| AT4G03250 | 0.098184037 | 0.00000000 | 0.014365588 | 0.000000000 | 0.004780115 | 0.000000000 | 0.012475395 | 0.000000000 | 0.060268203 | 0.000000000 | 0.006294737 | AT4G03250 | AT4G03250 |
| TCP24 | 0.059879916 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.059879916 | 0.000000000 | 0.000000000 | AT1G30210 | TCP24 |
| AT1G68030 | 0.036969277 | 0.00000000 | 0.000000000 | 0.000000000 | 0.002868069 | 0.000000000 | 0.004059424 | 0.000000000 | 0.030041784 | 0.000000000 | 0.000000000 | AT1G68030 | AT1G68030 |
| WRKY50 | 0.027779512 | 0.00000000 | 0.000000000 | 0.000000000 | 0.002868069 | 0.000000000 | 0.003185921 | 0.000000000 | 0.017947116 | 0.000000000 | 0.003778406 | AT5G26170 | WRKY50 |
| AT3G52270 | 0.014641262 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.014641262 | 0.000000000 | 0.000000000 | AT3G52270 | AT3G52270 |
| OFP11 | 0.007417382 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.007417382 | 0.000000000 | 0.000000000 | AT4G14860 | OFP11 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(phl_rank[1:10,], aes(x=reorder(GeneName, phl, decreasing = FALSE), y=phl)) + geom_point(size=4)+
labs(title="Phloem-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(phl_rank,"Phloem_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- phl_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Phloem ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
xyl_rank <- bc_rank[which(bc_rank$xyl*2 > bc_rank$all),]%>% arrange(desc(xyl))
xyl_rank$GeneName <- rownames(xyl_rank)
xyl_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| AT1G68810 | 11.536622 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.32495975 | 11.041633 | 0.17002908 | 0.000000000 | 0.00000000 | AT1G68810 | AT1G68810 |
| VND2 | 9.638343 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.02646882 | 9.611874 | 0.00000000 | 0.000000000 | 0.00000000 | AT4G36160 | VND2 |
| MYB46 | 8.777686 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 8.777686 | 0.00000000 | 0.000000000 | 0.00000000 | AT5G12870 | MYB46 |
| ATHB-15 | 13.243226 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.59770967 | 3.71766157 | 8.558721 | 0.36913403 | 0.000000000 | 0.00000000 | AT1G52150 | ATHB-15 |
| DOF2 | 10.249995 | 0.00000000 | 0.000000000 | 0.351580305 | 1.282458163 | 0.00000000 | 0.00000000 | 8.527854 | 0.00000000 | 0.050294993 | 0.03780762 | AT3G21270 | DOF2 |
| MYB83 | 8.033038 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 8.033038 | 0.00000000 | 0.000000000 | 0.00000000 | AT3G08500 | MYB83 |
| VND3 | 7.788913 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.03811280 | 7.750800 | 0.00000000 | 0.000000000 | 0.00000000 | AT5G66300 | VND3 |
| AT1G66810 | 7.561682 | 0.01586414 | 0.026086404 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 7.400563 | 0.00000000 | 0.119168117 | 0.00000000 | AT1G66810 | AT1G66810 |
| VND7 | 7.301973 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 7.301973 | 0.00000000 | 0.000000000 | 0.00000000 | AT1G71930 | VND7 |
| IAA6 | 7.188061 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.01379361 | 7.174267 | 0.00000000 | 0.000000000 | 0.00000000 | AT1G52830 | IAA6 |
| ZHD3 | 7.143422 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 7.143422 | 0.00000000 | 0.000000000 | 0.00000000 | AT2G02540 | ZHD3 |
| IAA31 | 10.900804 | 0.00000000 | 2.802604101 | 0.000000000 | 0.000000000 | 0.03476655 | 0.63950508 | 7.043569 | 0.38035904 | 0.000000000 | 0.00000000 | AT3G17600 | IAA31 |
| PHB | 10.332204 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.34165790 | 1.93126800 | 6.595116 | 1.15678338 | 0.105396182 | 0.20198271 | AT2G34710 | PHB |
| IAA8 | 10.422576 | 0.24034784 | 0.000000000 | 0.008117677 | 0.120650839 | 0.28653914 | 1.57914862 | 6.466031 | 0.28265168 | 0.888256807 | 0.55083188 | AT2G22670 | IAA8 |
| VND4 | 6.347801 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 6.347801 | 0.00000000 | 0.000000000 | 0.00000000 | AT1G12260 | VND4 |
| BHLH32 | 10.652133 | 0.14112463 | 0.000000000 | 0.142577807 | 0.160337883 | 3.14212784 | 1.16852421 | 5.897440 | 0.00000000 | 0.000000000 | 0.00000000 | AT3G25710 | BHLH32 |
| VND5 | 5.622524 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 5.622524 | 0.00000000 | 0.000000000 | 0.00000000 | AT1G62700 | VND5 |
| XND1 | 5.577439 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.06468006 | 5.512758 | 0.00000000 | 0.000000000 | 0.00000000 | AT5G64530 | XND1 |
| VND1 | 5.298823 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 5.298823 | 0.00000000 | 0.000000000 | 0.00000000 | AT2G18060 | VND1 |
| AT1G68200 | 5.259217 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 5.259217 | 0.00000000 | 0.000000000 | 0.00000000 | AT1G68200 | AT1G68200 |
| HB31 | 5.157856 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 5.157856 | 0.00000000 | 0.000000000 | 0.00000000 | AT1G14440 | HB31 |
| LBD31 | 4.894236 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 4.894236 | 0.00000000 | 0.000000000 | 0.00000000 | AT4G00210 | LBD31 |
| NAC075 | 9.054390 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.35307753 | 0.21412043 | 4.541242 | 3.90193131 | 0.005966671 | 0.03805185 | AT4G29230 | NAC075 |
| HAT14 | 5.037822 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.08900348 | 0.54526568 | 4.403553 | 0.00000000 | 0.000000000 | 0.00000000 | AT5G06710 | HAT14 |
| LBD18 | 4.292386 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 4.226754 | 0.00000000 | 0.013799569 | 0.05183261 | AT2G45420 | LBD18 |
| ASL9 | 5.441949 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.08214788 | 0.60827844 | 3.854973 | 0.89655011 | 0.000000000 | 0.00000000 | AT1G16530 | ASL9 |
| NAC050 | 4.775704 | 0.04478520 | 0.003293898 | 0.000000000 | 0.003824092 | 0.00000000 | 0.00000000 | 3.778609 | 0.17050597 | 0.273912293 | 0.50077366 | AT3G10480 | NAC050 |
| AT1G27660 | 6.418503 | 0.00000000 | 0.000000000 | 0.016139067 | 0.022789488 | 1.53079207 | 0.88450150 | 3.726692 | 0.23758866 | 0.000000000 | 0.00000000 | AT1G27660 | AT1G27660 |
| JLO | 3.741622 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | 3.697310 | 0.00000000 | 0.013799569 | 0.03051252 | AT4G00220 | JLO |
| AP3 | 3.754440 | 0.00000000 | 0.000000000 | 0.000000000 | 0.022734174 | 0.00000000 | 0.02203160 | 3.618079 | 0.09159528 | 0.000000000 | 0.00000000 | AT3G54340 | AP3 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| AT1G24610 | 1.28532295 | 0.00000000 | 0.027324573 | 0.000000000 | 0.018993758 | 0.052527858 | 0.007418725 | 1.09533515 | 0.048403747 | 0.014273050 | 0.02104609 | AT1G24610 | AT1G24610 |
| AT1G26610 | 1.01572276 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.01572276 | 0.000000000 | 0.000000000 | 0.00000000 | AT1G26610 | AT1G26610 |
| BZIP49 | 0.98878988 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.98878988 | 0.000000000 | 0.000000000 | 0.00000000 | AT3G56660 | BZIP49 |
| AT1G21780 | 1.87033822 | 0.05770617 | 0.039336317 | 0.000000000 | 0.033268527 | 0.002863808 | 0.053975350 | 0.94878270 | 0.061103284 | 0.252282991 | 0.42101907 | AT1G21780 | AT1G21780 |
| IWS1 | 1.72910671 | 0.06241160 | 0.063762795 | 0.034452658 | 0.135643262 | 0.101251515 | 0.142644279 | 0.93914856 | 0.129202290 | 0.000000000 | 0.12058975 | AT1G32130 | IWS1 |
| AT5G03500 | 1.59794087 | 0.12729866 | 0.210505817 | 0.008290378 | 0.139656952 | 0.027803453 | 0.075780962 | 0.91150633 | 0.059498573 | 0.000000000 | 0.03759974 | AT5G03500 | AT5G03500 |
| AT4G19630 | 1.51504406 | 0.20687737 | 0.127747630 | 0.026834254 | 0.050262016 | 0.211076971 | 0.000000000 | 0.89224582 | 0.000000000 | 0.000000000 | 0.00000000 | AT4G19630 | AT4G19630 |
| AT3G60580 | 1.38960450 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.367576083 | 0.118863217 | 0.88867730 | 0.014487896 | 0.000000000 | 0.00000000 | AT3G60580 | AT3G60580 |
| AT3G10470 | 1.21130906 | 0.00000000 | 0.358628010 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.85268105 | 0.000000000 | 0.000000000 | 0.00000000 | AT3G10470 | AT3G10470 |
| AL2 | 1.44523637 | 0.00000000 | 0.073288053 | 0.033779102 | 0.043741070 | 0.048654959 | 0.055607945 | 0.84003587 | 0.133358571 | 0.017126642 | 0.19964416 | AT3G11200 | AL2 |
| HB34 | 0.96786493 | 0.01227990 | 0.017801472 | 0.000000000 | 0.008604207 | 0.000000000 | 0.044269749 | 0.73467419 | 0.146148303 | 0.004087115 | 0.00000000 | AT3G28920 | HB34 |
| BZIP24 | 0.69473539 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.036501552 | 0.63058514 | 0.027648698 | 0.000000000 | 0.00000000 | AT3G51960 | BZIP24 |
| GIF3 | 0.68630806 | 0.00000000 | 0.000000000 | 0.004145189 | 0.030195385 | 0.000000000 | 0.041122758 | 0.61084473 | 0.000000000 | 0.000000000 | 0.00000000 | AT4G00850 | GIF3 |
| AT5G06770 | 0.82709697 | 0.02788150 | 0.034907787 | 0.031156037 | 0.072925874 | 0.003045749 | 0.002127720 | 0.59147018 | 0.004071634 | 0.018644751 | 0.04086574 | AT5G06770 | AT5G06770 |
| AT3G22100 | 0.68127060 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.55474879 | 0.126521815 | 0.000000000 | 0.00000000 | AT3G22100 | AT3G22100 |
| FBH2 | 0.92274260 | 0.03968020 | 0.008404289 | 0.014127349 | 0.029444435 | 0.016600778 | 0.012369000 | 0.54712225 | 0.179537970 | 0.026085088 | 0.04937124 | AT4G09180 | FBH2 |
| AT3G49930 | 0.71613741 | 0.01202537 | 0.049425790 | 0.047856345 | 0.097644391 | 0.010539127 | 0.000000000 | 0.45993985 | 0.028475042 | 0.000000000 | 0.01023149 | AT3G49930 | AT3G49930 |
| JAZ11 | 0.76266853 | 0.05672855 | 0.026775396 | 0.014127349 | 0.031067421 | 0.016929972 | 0.010724510 | 0.39486179 | 0.192179273 | 0.005966671 | 0.01330760 | AT3G43440 | JAZ11 |
| PIF4 | 0.43532347 | 0.00000000 | 0.000000000 | 0.000000000 | 0.003824092 | 0.000000000 | 0.005511606 | 0.37184351 | 0.054144264 | 0.000000000 | 0.00000000 | AT2G43010 | PIF4 |
| AT5G18090 | 0.52826362 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.31818293 | 0.105024189 | 0.069530228 | 0.03552627 | AT5G18090 | AT5G18090 |
| ARR15 | 0.29865152 | 0.00000000 | 0.000000000 | 0.015444015 | 0.000000000 | 0.000000000 | 0.000000000 | 0.28320751 | 0.000000000 | 0.000000000 | 0.00000000 | AT1G74890 | ARR15 |
| AGL64 | 0.27514793 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.27514793 | 0.000000000 | 0.000000000 | 0.00000000 | AT1G29962 | AGL64 |
| AT3G45880 | 0.41074758 | 0.08731405 | 0.028867289 | 0.000000000 | 0.011472275 | 0.000000000 | 0.000000000 | 0.24281748 | 0.040276483 | 0.000000000 | 0.00000000 | AT3G45880 | AT3G45880 |
| AT1G24040 | 0.27513044 | 0.00000000 | 0.000000000 | 0.000000000 | 0.002889449 | 0.000000000 | 0.000000000 | 0.21701485 | 0.000000000 | 0.055226142 | 0.00000000 | AT1G24040 | AT1G24040 |
| AT1G76870 | 0.33154241 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.007189877 | 0.051141693 | 0.21518991 | 0.058020931 | 0.000000000 | 0.00000000 | AT1G76870 | AT1G76870 |
| AT2G22200 | 0.20417819 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.15794307 | 0.000000000 | 0.046235127 | 0.00000000 | AT2G22200 | AT2G22200 |
| OFP10 | 0.09384749 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.09384749 | 0.000000000 | 0.000000000 | 0.00000000 | AT5G22240 | OFP10 |
| AT4G08250 | 0.10688739 | 0.00000000 | 0.012352944 | 0.000000000 | 0.024140650 | 0.000000000 | 0.000000000 | 0.07039380 | 0.000000000 | 0.000000000 | 0.00000000 | AT4G08250 | AT4G08250 |
| ORC1A | 0.05185896 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.03223832 | 0.000000000 | 0.019620644 | 0.00000000 | AT4G14700 | ORC1A |
| AT5G46915 | 0.04334105 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.015078047 | 0.000000000 | 0.02826301 | 0.000000000 | 0.000000000 | 0.00000000 | AT5G46915 | AT5G46915 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(xyl_rank[1:10,], aes(x=reorder(GeneName, xyl, decreasing = FALSE), y=xyl)) + geom_point(size=4)+
labs(title="Xylem-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(xyl_rank,"Xylem_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- xyl_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Xylem ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
lrc_rank <- bc_rank[which(bc_rank$lrc*2 > bc_rank$all),]%>% arrange(desc(lrc))
lrc_rank$GeneName <- rownames(lrc_rank)
lrc_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| AT1G68920 | 12.028456518 | 0.80269789 | 0.066031541 | 0.35244162 | 0.129029370 | 0.000000000 | 0.000000000 | 0.00000000 | 0.050039116 | 6.069123864 | 4.55909312 | AT1G68920 | AT1G68920 |
| ANL2 | 9.794258630 | 2.66677616 | 0.479300264 | 0.57303214 | 0.151216222 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 4.977955879 | 0.94597797 | AT4G00730 | ANL2 |
| OFP6 | 4.865209570 | 0.81111328 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 4.031024308 | 0.02307198 | AT3G52525 | OFP6 |
| ASL1 | 7.139711374 | 0.92904994 | 0.160306017 | 0.21414076 | 0.080168941 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 3.587946721 | 2.16809900 | AT5G66870 | ASL1 |
| AT1G05805 | 6.422509285 | 0.53216520 | 0.286505224 | 0.08255675 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 3.228166038 | 2.29311608 | AT1G05805 | AT1G05805 |
| AT1G69030 | 5.649837921 | 0.41092076 | 0.120856558 | 0.16213030 | 0.301310724 | 0.032585593 | 0.007205912 | 0.79317340 | 0.143402744 | 3.134753625 | 0.54349831 | AT1G69030 | AT1G69030 |
| AT5G48560 | 5.877041418 | 0.56988054 | 0.028008727 | 0.16405786 | 0.095136546 | 0.038354731 | 0.138869733 | 0.00000000 | 0.174961065 | 3.118548124 | 1.54922409 | AT5G48560 | AT5G48560 |
| AIL5 | 5.291341118 | 0.47478752 | 0.016601883 | 0.10745552 | 0.040084471 | 0.000000000 | 0.022200745 | 0.00000000 | 0.000000000 | 3.104543481 | 1.52566750 | AT5G57390 | AIL5 |
| WRKY11 | 5.311201179 | 0.75893219 | 0.333131627 | 0.17338140 | 0.166824582 | 0.111499756 | 0.260780670 | 0.20035394 | 0.055042565 | 2.793604747 | 0.45764970 | AT4G31550 | WRKY11 |
| AT3G60670 | 4.491201102 | 0.19804070 | 0.000000000 | 0.09818241 | 0.003824092 | 0.000000000 | 0.004118849 | 0.00000000 | 0.000000000 | 2.628930196 | 1.55810485 | AT3G60670 | AT3G60670 |
| LBD4 | 4.621108722 | 0.73410069 | 0.039018397 | 0.26332825 | 0.148908920 | 0.000000000 | 0.000000000 | 0.00000000 | 0.018969584 | 2.348401137 | 1.06838175 | AT1G31320 | LBD4 |
| AT1G21000 | 4.413675536 | 0.18764047 | 0.053546095 | 0.00000000 | 0.008604207 | 0.208504162 | 0.434159716 | 0.00000000 | 0.359134919 | 2.319946975 | 0.84213899 | AT1G21000 | AT1G21000 |
| AT5G62610 | 4.098912215 | 0.52985201 | 0.169729962 | 0.15988380 | 0.157210322 | 0.023803603 | 0.000000000 | 0.03932829 | 0.123812281 | 2.152560271 | 0.74273168 | AT5G62610 | AT5G62610 |
| AT1G09250 | 4.002871998 | 0.44767014 | 0.063171757 | 0.31825713 | 0.257940443 | 0.069915289 | 0.041396054 | 0.00000000 | 0.100285399 | 2.075494388 | 0.62874139 | AT1G09250 | AT1G09250 |
| GRF2 | 2.386541167 | 0.37199083 | 0.163265493 | 0.15298413 | 0.061251027 | 0.026649615 | 0.000000000 | 0.00000000 | 0.023895361 | 1.487990391 | 0.09851432 | AT4G37740 | GRF2 |
| HSF A4A | 2.228440554 | 0.06769198 | 0.018463845 | 0.06155743 | 0.159372779 | 0.007012623 | 0.023786766 | 0.00000000 | 0.020296272 | 1.173419793 | 0.69683906 | AT4G18880 | HSF A4A |
| AGL20 | 1.676238446 | 0.05574800 | 0.000000000 | 0.03256699 | 0.023600954 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 1.146423683 | 0.41789882 | AT2G45660 | AGL20 |
| TOE3 | 2.056734382 | 0.11261032 | 0.000000000 | 0.31506886 | 0.125307966 | 0.000000000 | 0.004059424 | 0.02406962 | 0.028609874 | 1.081520509 | 0.36548781 | AT5G67180 | TOE3 |
| NAC016 | 1.560401930 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.801524240 | 0.75887769 | AT1G34180 | NAC016 |
| MYB3R-4 | 1.184472030 | 0.12311429 | 0.000000000 | 0.12720903 | 0.031963529 | 0.044776504 | 0.016561928 | 0.00000000 | 0.007808814 | 0.659143499 | 0.17389444 | AT5G11510 | MYB3R-4 |
| AGL94 | 1.221091071 | 0.04501335 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.615888474 | 0.56018925 | AT1G69540 | AGL94 |
| HDG2 | 0.426117788 | 0.05843617 | 0.016601883 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.248885013 | 0.10219472 | AT1G05230 | HDG2 |
| AT2G20110 | 0.282612672 | 0.01611099 | 0.000000000 | 0.01079147 | 0.006692161 | 0.000000000 | 0.010963788 | 0.00000000 | 0.000000000 | 0.142870875 | 0.09518338 | AT2G20110 | AT2G20110 |
| AT5G25790 | 0.198890384 | 0.00000000 | 0.000000000 | 0.00000000 | 0.006692161 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.105738326 | 0.08645990 | AT5G25790 | AT5G25790 |
| NAC063 | 0.121166254 | 0.02290884 | 0.003293898 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00755784 | 0.000000000 | 0.087405673 | 0.00000000 | AT3G55210 | NAC063 |
| HSFC1 | 0.105923308 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.008592402 | 0.018994153 | 0.00000000 | 0.007815022 | 0.053203407 | 0.01731832 | AT3G24520 | HSFC1 |
| AT3G19184 | 0.079582042 | 0.00000000 | 0.019069529 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.014153900 | 0.046358612 | 0.00000000 | AT3G19184 | AT3G19184 |
| AT2G23060 | 0.005360395 | 0.00000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.005360395 | 0.00000000 | AT2G23060 | AT2G23060 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(lrc_rank[1:10,], aes(x=reorder(GeneName, lrc, decreasing = FALSE), y=lrc)) + geom_point(size=4)+
labs(title="LRC-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(lrc_rank,"LRC_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- lrc_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Lateral Root Cap ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
col_rank <- bc_rank[which(bc_rank$col*2 > bc_rank$all),]%>% arrange(desc(col))
col_rank$GeneName <- rownames(col_rank)
col_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <chr> | |
| NAC042 | 15.848132176 | 0.013811893 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 6.854929780 | 8.979390503 | AT2G43000 | NAC042 |
| RAP2.4 | 10.006093142 | 0.186297480 | 0.008448429 | 0.282168255 | 0.182106509 | 0.116762648 | 0.290389873 | 0.178080743 | 0.096254210 | 2.979364487 | 5.686220508 | AT1G78080 | RAP2.4 |
| LBD41 | 9.456000605 | 0.307008709 | 0.191520974 | 0.000000000 | 0.070337772 | 0.069542655 | 0.139797662 | 0.003778920 | 0.000000000 | 3.469790935 | 5.204222979 | AT3G02550 | LBD41 |
| AT3G52440 | 9.429183334 | 0.985446142 | 0.000000000 | 0.172878368 | 0.012611943 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 3.236305265 | 5.021941616 | AT3G52440 | AT3G52440 |
| WRKY33 | 8.874355007 | 0.452522181 | 0.137972930 | 0.898694396 | 0.359952109 | 0.061746041 | 0.019995697 | 0.000000000 | 0.000000000 | 2.119999332 | 4.823472321 | AT2G38470 | WRKY33 |
| FBH4 | 8.394265863 | 0.095062463 | 0.016515136 | 0.377258006 | 0.020283339 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 3.482554761 | 4.402592158 | AT2G42280 | FBH4 |
| NAM | 5.032279576 | 0.049435808 | 0.000000000 | 0.087143552 | 0.012428298 | 0.011567265 | 0.035736305 | 0.000000000 | 0.000000000 | 1.742243550 | 3.093724799 | AT1G52880 | NAM |
| MYB55 | 5.168010880 | 0.000000000 | 0.000000000 | 0.204637710 | 0.037920439 | 0.190036368 | 0.542549136 | 0.000000000 | 0.670759127 | 0.556416987 | 2.965691113 | AT4G01680 | MYB55 |
| ARF10 | 5.331093835 | 0.311459849 | 0.005195039 | 0.063037907 | 0.091195214 | 0.000000000 | 0.000000000 | 0.052948378 | 0.059813008 | 1.805865438 | 2.941579001 | AT2G28350 | ARF10 |
| MIF3 | 5.021811302 | 0.000000000 | 0.000000000 | 0.000000000 | 0.177225730 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.980454559 | 2.864131012 | AT1G18835 | MIF3 |
| WRKY26 | 4.693762837 | 0.085164280 | 0.048726749 | 0.000000000 | 0.000000000 | 0.124044165 | 0.090023319 | 0.000000000 | 0.077082119 | 1.454293162 | 2.814429043 | AT5G07100 | WRKY26 |
| BZIP25 | 3.834485078 | 0.354132474 | 0.090644091 | 0.217755390 | 0.126487469 | 0.014011226 | 0.017541971 | 0.000000000 | 0.041656730 | 0.635647021 | 2.336608705 | AT3G54620 | BZIP25 |
| AT2G41835 | 2.692651000 | 0.105482633 | 0.013599328 | 0.000000000 | 0.008604207 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.497079177 | 2.067885655 | AT2G41835 | AT2G41835 |
| TGA7 | 3.906170154 | 0.095375083 | 0.182361754 | 0.769839262 | 0.009767087 | 0.000000000 | 0.006904364 | 0.000000000 | 0.000000000 | 0.875760393 | 1.966162211 | AT1G77920 | TGA7 |
| AT3G25790 | 3.229468530 | 0.128992325 | 0.026093609 | 0.215806365 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.930766326 | 1.927809906 | AT3G25790 | AT3G25790 |
| SNI1 | 2.546469452 | 0.000000000 | 0.000000000 | 0.024256744 | 0.000000000 | 0.000000000 | 0.011021681 | 0.453197944 | 0.108123713 | 0.271128853 | 1.678740517 | AT4G18470 | SNI1 |
| NAC052 | 2.982878435 | 0.124093179 | 0.006325287 | 0.012262866 | 0.049810258 | 0.021751524 | 0.045356986 | 0.104789021 | 0.025698804 | 1.016760611 | 1.576029899 | AT3G10490 | NAC052 |
| RR1 | 2.566895589 | 0.214778894 | 0.057848262 | 0.167176491 | 0.027992494 | 0.026105660 | 0.025236475 | 0.003778920 | 0.074660945 | 0.401287262 | 1.568030186 | AT3G16857 | RR1 |
| HMG | 2.763025764 | 0.059576067 | 0.023371173 | 0.357420825 | 0.169862373 | 0.148964595 | 0.110386580 | 0.011336759 | 0.116902434 | 0.283892260 | 1.481312697 | AT3G28730 | HMG |
| TGA4 | 2.482817925 | 0.055247572 | 0.072129849 | 0.209752180 | 0.091251579 | 0.068634856 | 0.202400789 | 0.000000000 | 0.234746171 | 0.266108661 | 1.282546268 | AT5G10030 | TGA4 |
| AT2G42300 | 2.238305659 | 0.098758750 | 0.025975195 | 0.094449464 | 0.002868069 | 0.000000000 | 0.000000000 | 0.000000000 | 0.015066107 | 0.774068687 | 1.227119386 | AT2G42300 | AT2G42300 |
| TLP7 | 2.134130449 | 0.061285337 | 0.031008740 | 0.129016209 | 0.037198088 | 0.008244660 | 0.057619057 | 0.030871090 | 0.073595932 | 0.537622092 | 1.167669243 | AT1G53320 | TLP7 |
| BRM | 2.268815558 | 0.117827795 | 0.026951453 | 0.246565813 | 0.079885378 | 0.026107770 | 0.052947449 | 0.007557840 | 0.070781273 | 0.487394849 | 1.152795939 | AT2G46020 | BRM |
| SYD | 2.204603753 | 0.094800415 | 0.007096180 | 0.040777167 | 0.049819092 | 0.083455852 | 0.113237151 | 0.021369847 | 0.199344946 | 0.459097888 | 1.135605216 | AT2G28290 | SYD |
| CHR11 | 1.951484413 | 0.051771620 | 0.007980554 | 0.007793918 | 0.039761725 | 0.070375125 | 0.090240263 | 0.126614290 | 0.174916038 | 0.356507473 | 1.025523407 | AT3G06400 | CHR11 |
| EIN3 | 1.538177010 | 0.077061788 | 0.032686672 | 0.088661842 | 0.046762834 | 0.004849074 | 0.021091991 | 0.012574383 | 0.030242517 | 0.286814863 | 0.937431046 | AT3G20770 | EIN3 |
| ATRX | 1.726883317 | 0.045821061 | 0.012549096 | 0.030161508 | 0.049839236 | 0.087337280 | 0.091132433 | 0.013845031 | 0.157725436 | 0.305210413 | 0.933261821 | AT1G08600 | ATRX |
| AT1G02080 | 1.791566361 | 0.080962172 | 0.024206446 | 0.103334933 | 0.029782074 | 0.031449072 | 0.061932325 | 0.110579720 | 0.183101466 | 0.266337879 | 0.899880274 | AT1G02080 | AT1G02080 |
| PC-MYB1 | 1.429478998 | 0.083408050 | 0.021664531 | 0.061121765 | 0.030588131 | 0.000000000 | 0.002726091 | 0.010099136 | 0.062012385 | 0.349432679 | 0.808426232 | AT4G32730 | PC-MYB1 |
| AT2G44430 | 1.589365661 | 0.130997472 | 0.069199895 | 0.132295825 | 0.093511565 | 0.000000000 | 0.000000000 | 0.030981837 | 0.012891105 | 0.317526105 | 0.801961857 | AT2G44430 | AT2G44430 |
| SDG2 | 1.390375312 | 0.059448729 | 0.053174183 | 0.122279279 | 0.053853321 | 0.008917847 | 0.024841387 | 0.007557840 | 0.054941038 | 0.224846411 | 0.780515277 | AT4G15180 | SDG2 |
| EICBP.B | 1.472034674 | 0.073448730 | 0.051128746 | 0.202014821 | 0.050546226 | 0.004604770 | 0.006329047 | 0.018861575 | 0.115464069 | 0.210166015 | 0.739470676 | AT5G09410 | EICBP.B |
| AT5G14140 | 1.330142648 | 0.000000000 | 0.062621708 | 0.019294295 | 0.105427844 | 0.012460976 | 0.008476926 | 0.000000000 | 0.055676774 | 0.355338767 | 0.710845358 | AT5G14140 | AT5G14140 |
| AT5G65910 | 1.309393705 | 0.056069380 | 0.030950543 | 0.039829220 | 0.101513043 | 0.042078039 | 0.029737762 | 0.112702700 | 0.060372148 | 0.174146154 | 0.661994717 | AT5G65910 | AT5G65910 |
| MBD9 | 1.195668436 | 0.119929174 | 0.031589336 | 0.000000000 | 0.007648184 | 0.000000000 | 0.019765082 | 0.005049568 | 0.045507686 | 0.364661169 | 0.601518238 | AT3G01460 | MBD9 |
| E2F1 | 0.953848255 | 0.031720267 | 0.058304625 | 0.005836971 | 0.009560229 | 0.015083754 | 0.007171406 | 0.000000000 | 0.030631302 | 0.303211449 | 0.492328251 | AT5G22220 | E2F1 |
| DRIP2 | 0.696898860 | 0.011770842 | 0.008864929 | 0.000000000 | 0.002868069 | 0.002982303 | 0.043636687 | 0.011336759 | 0.007830786 | 0.132174319 | 0.475434165 | AT2G30580 | DRIP2 |
| AT3G08505 | 0.744365710 | 0.000000000 | 0.043199141 | 0.000000000 | 0.002868069 | 0.008920351 | 0.043766669 | 0.000000000 | 0.000000000 | 0.232433819 | 0.413177661 | AT3G08505 | AT3G08505 |
| AT3G54460 | 0.707080513 | 0.011770842 | 0.005195039 | 0.005836971 | 0.030300456 | 0.011397451 | 0.019803161 | 0.000000000 | 0.000000000 | 0.230896865 | 0.391879727 | AT3G54460 | AT3G54460 |
| AT4G13040 | 0.553191474 | 0.035265618 | 0.039379131 | 0.036986217 | 0.010723110 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.103130348 | 0.327707050 | AT4G13040 | AT4G13040 |
| RING1 | 0.306628935 | 0.006043877 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.013431320 | 0.000000000 | 0.000000000 | 0.097875315 | 0.189278424 | AT5G10380 | RING1 |
| BPC7 | 0.371493013 | 0.029533810 | 0.000000000 | 0.000000000 | 0.003824092 | 0.000000000 | 0.005392758 | 0.000000000 | 0.000000000 | 0.144092060 | 0.188650294 | AT2G35550 | BPC7 |
| NF-YC12 | 0.111223991 | 0.000000000 | 0.000000000 | 0.007722008 | 0.000000000 | 0.000000000 | 0.005860963 | 0.000000000 | 0.000000000 | 0.017402388 | 0.080238632 | AT5G38140 | NF-YC12 |
| AT2G33550 | 0.081155475 | 0.000000000 | 0.004686656 | 0.000000000 | 0.003824092 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.009696242 | 0.062948486 | AT2G33550 | AT2G33550 |
| AT1G18560 | 0.074964285 | 0.000000000 | 0.003293898 | 0.000000000 | 0.002868069 | 0.000000000 | 0.009032084 | 0.000000000 | 0.006275523 | 0.010779031 | 0.042715680 | AT1G18560 | AT1G18560 |
| AT4G36050 | 0.060859671 | 0.000000000 | 0.000000000 | 0.000000000 | 0.006692161 | 0.000000000 | 0.010144816 | 0.000000000 | 0.004456859 | 0.000000000 | 0.039565836 | AT4G36050 | AT4G36050 |
| BEH1 | 0.031272143 | 0.000000000 | 0.005961299 | 0.000000000 | 0.002868069 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.005921977 | 0.016520798 | AT3G50750 | BEH1 |
| AT5G08520 | 0.008843193 | 0.000000000 | 0.000000000 | 0.000000000 | 0.003824092 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.005019101 | AT5G08520 | AT5G08520 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(col_rank[1:10,], aes(x=reorder(GeneName, col, decreasing = FALSE), y=col)) + geom_point(size=4)+
labs(title="Columella-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(col_rank,"Columella_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- col_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Columella ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
bc_rank <- bc_rank %>% mutate(ground=cor+end, epi=atri+tri, stele=per+pro+xyl+phl, epilrc=atri+tri+lrc, rc=lrc+col)
head(bc_rank)
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | ground | epi | stele | epilrc | rc | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | |
| BZIP9 | 31.42213 | 0.000000 | 0.000000 | 0.00000000 | 0.005736138 | 8.55316613 | 11.88088107 | 0.02003315 | 10.9623184 | 0.000000 | 0.000000 | AT5G24800 | 0.005736138 | 0.000000 | 31.41639871 | 0.00000 | 0.000000 |
| AT3G43430 | 29.05965 | 0.000000 | 0.000000 | 0.00544388 | 0.029360833 | 9.20656526 | 11.24626128 | 1.83863137 | 6.7333880 | 0.000000 | 0.000000 | AT3G43430 | 0.034804713 | 0.000000 | 29.02484588 | 0.00000 | 0.000000 |
| PLT1 | 23.97514 | 3.940608 | 0.000000 | 2.00953127 | 1.492057686 | 0.05699842 | 0.00000000 | 0.00000000 | 0.0000000 | 9.148008 | 7.327940 | AT3G20840 | 3.501588961 | 3.940608 | 0.05699842 | 13.08862 | 16.475948 |
| HAT7 | 33.13977 | 6.200914 | 5.547329 | 8.04274907 | 5.877125010 | 1.24427942 | 0.00000000 | 0.00000000 | 0.0122843 | 4.284922 | 1.930171 | AT5G15150 | 13.919874084 | 11.748243 | 1.25656372 | 16.03317 | 6.215093 |
| MYB36 | 20.57418 | 0.000000 | 0.000000 | 6.29093689 | 10.748544272 | 3.53469871 | 0.00000000 | 0.00000000 | 0.0000000 | 0.000000 | 0.000000 | AT5G57620 | 17.039481158 | 0.000000 | 3.53469871 | 0.00000 | 0.000000 |
| GATA2 | 33.12273 | 6.623792 | 6.596557 | 2.46621779 | 2.051664424 | 0.80375905 | 0.03881894 | 0.09406244 | 0.1559529 | 12.103509 | 2.188393 | AT2G45050 | 4.517882216 | 13.220349 | 1.09259336 | 25.32386 | 14.291902 |
ground_rank <- bc_rank[which(bc_rank$ground*2 > bc_rank$all),]%>% arrange(desc(ground))
ground_rank <- ground_rank[-c(match(rownames(cor_rank), rownames(ground_rank)),match(rownames(end_rank), rownames(ground_rank))),]
ground_rank$GeneName <- rownames(ground_rank)
ground_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | ground | epi | stele | epilrc | rc | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | |
| MYB12 | 23.6925714 | 0.086429636 | 0.116639239 | 7.788192391 | 5.78330037 | 1.929749529 | 0.516205906 | 3.371248525 | 1.210403057 | 0.110529735 | 2.779872975 | AT2G47460 | 13.57149276 | 0.203068875 | 7.027607017 | 0.31359861 | 2.890402710 | MYB12 |
| MYB3 | 11.8841880 | 0.516196596 | 0.089796448 | 2.733348149 | 5.59048060 | 2.347020632 | 0.023860054 | 0.392757518 | 0.051272502 | 0.135677055 | 0.003778406 | AT1G22640 | 8.32382874 | 0.605993044 | 2.814910706 | 0.74167010 | 0.139455462 | MYB3 |
| JKD | 8.4732071 | 0.000000000 | 0.000000000 | 3.707652355 | 2.97524102 | 0.046405172 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.743908530 | AT5G03150 | 6.68289338 | 0.000000000 | 0.046405172 | 0.00000000 | 1.743908530 | JKD |
| AN3 | 9.1822731 | 1.164651915 | 0.192213903 | 2.337373113 | 3.15346845 | 2.100233534 | 0.058317549 | 0.000000000 | 0.058683307 | 0.112312266 | 0.005019101 | AT5G28640 | 5.49084156 | 1.356865818 | 2.217234390 | 1.46917808 | 0.117331367 | AN3 |
| ARR3 | 8.5913166 | 0.277809106 | 0.042398606 | 2.342944255 | 3.13353902 | 1.024916677 | 0.292536040 | 0.000000000 | 0.761437377 | 0.227870782 | 0.487864717 | AT1G59940 | 5.47648327 | 0.320207712 | 2.078890094 | 0.54807849 | 0.715735499 | ARR3 |
| AtHB23 | 8.8753093 | 0.501488974 | 0.374681517 | 3.154663839 | 1.83622525 | 1.774905009 | 0.759227164 | 0.123371046 | 0.238366599 | 0.047751144 | 0.064628773 | AT1G26960 | 4.99088909 | 0.876170491 | 2.895869819 | 0.92392163 | 0.112379917 | AtHB23 |
| GATA16 | 9.1755332 | 0.000000000 | 0.000000000 | 2.717450549 | 1.93427924 | 1.963803057 | 0.385471434 | 0.600895613 | 0.024737577 | 0.274582712 | 1.274312995 | AT5G49300 | 4.65172978 | 0.000000000 | 2.974907680 | 0.27458271 | 1.548895708 | GATA16 |
| ULT1 | 7.0016708 | 0.112700338 | 0.004686656 | 2.229074863 | 2.07787649 | 1.582433859 | 0.147766912 | 0.195664304 | 0.032078314 | 0.394481296 | 0.224907778 | AT4G28190 | 4.30695135 | 0.117386994 | 1.957943389 | 0.51186829 | 0.619389073 | ULT1 |
| HSFB4 | 5.2735423 | 0.120861144 | 0.000000000 | 1.634055563 | 2.58265054 | 0.381517308 | 0.423129431 | 0.099979596 | 0.031348729 | 0.000000000 | 0.000000000 | AT1G46264 | 4.21670610 | 0.120861144 | 0.935975064 | 0.12086114 | 0.000000000 | HSFB4 |
| ABS2 | 7.5430799 | 0.116787466 | 0.027995342 | 2.404733477 | 1.38370900 | 0.157625686 | 0.031317493 | 0.544361549 | 0.263006040 | 0.397556402 | 2.215987470 | AT2G36080 | 3.78844248 | 0.144782808 | 0.996310768 | 0.54233921 | 2.613543872 | ABS2 |
| AT5G57150 | 6.2922314 | 0.150126218 | 0.000000000 | 0.974717001 | 2.56868894 | 0.666176661 | 0.326689893 | 0.000000000 | 1.395297246 | 0.107660702 | 0.102874696 | AT5G57150 | 3.54340595 | 0.150126218 | 2.388163800 | 0.25778692 | 0.210535398 | AT5G57150 |
| MNP | 5.7890576 | 0.455490525 | 0.076023492 | 1.575465392 | 1.53636438 | 0.261655240 | 0.085935005 | 1.649952441 | 0.148171124 | 0.000000000 | 0.000000000 | AT3G50870 | 3.11182978 | 0.531514017 | 2.145713810 | 0.53151402 | 0.000000000 | MNP |
| HB5 | 4.3101311 | 0.000000000 | 0.000000000 | 1.631499417 | 0.90681682 | 0.618155504 | 0.674749557 | 0.004983519 | 0.467666517 | 0.000000000 | 0.006259796 | AT5G65310 | 2.53831624 | 0.000000000 | 1.765555097 | 0.00000000 | 0.006259796 | HB5 |
| AT3G24120 | 2.9748807 | 0.000000000 | 0.000000000 | 1.318839111 | 0.94921303 | 0.443322301 | 0.199393514 | 0.000000000 | 0.046574013 | 0.000000000 | 0.017538693 | AT3G24120 | 2.26805214 | 0.000000000 | 0.689289829 | 0.00000000 | 0.017538693 | AT3G24120 |
| AT3G23690 | 4.4070459 | 0.174698758 | 0.007929803 | 0.704941693 | 1.53239725 | 0.800609034 | 0.425340033 | 0.207459739 | 0.515680653 | 0.035451259 | 0.002537712 | AT3G23690 | 2.23733895 | 0.182628561 | 1.949089458 | 0.21807982 | 0.037988971 | AT3G23690 |
| AT1G63100 | 3.1124480 | 0.465963596 | 0.112858909 | 1.432843966 | 0.79925969 | 0.086892337 | 0.000000000 | 0.000000000 | 0.000000000 | 0.214629549 | 0.000000000 | AT1G63100 | 2.23210365 | 0.578822505 | 0.086892337 | 0.79345205 | 0.214629549 | AT1G63100 |
| PRMT3 | 4.0160072 | 0.535116699 | 0.380272681 | 1.087282543 | 1.10717393 | 0.255490804 | 0.000000000 | 0.000000000 | 0.000000000 | 0.484268957 | 0.166401584 | AT3G12270 | 2.19445648 | 0.915389380 | 0.255490804 | 1.39965834 | 0.650670542 | PRMT3 |
| AT3G61420 | 3.5419499 | 1.163565877 | 0.161087741 | 1.539386008 | 0.62316908 | 0.014899816 | 0.022547350 | 0.000000000 | 0.000000000 | 0.000000000 | 0.017294004 | AT3G61420 | 2.16255508 | 1.324653618 | 0.037447166 | 1.32465362 | 0.017294004 | AT3G61420 |
| RGL3 | 3.8656758 | 0.148167809 | 0.071988745 | 1.829941208 | 0.17182469 | 0.000000000 | 0.005302323 | 0.040598935 | 0.000000000 | 0.333055643 | 1.264796477 | AT5G17490 | 2.00176590 | 0.220156554 | 0.045901257 | 0.55321220 | 1.597852120 | RGL3 |
| AT4G36860 | 2.9275705 | 0.033367005 | 0.000000000 | 0.691306976 | 0.94922066 | 0.055919455 | 0.046380543 | 0.537992075 | 0.198786042 | 0.142671389 | 0.271926374 | AT4G36860 | 1.64052763 | 0.033367005 | 0.839078116 | 0.17603839 | 0.414597763 | AT4G36860 |
| HB6 | 2.6007464 | 0.315425451 | 0.061080034 | 0.912825103 | 0.52862454 | 0.134608602 | 0.087486844 | 0.000000000 | 0.110169804 | 0.138287349 | 0.312238711 | AT2G22430 | 1.44144964 | 0.376505485 | 0.332265250 | 0.51479283 | 0.450526060 | HB6 |
| PS1 | 2.6530463 | 0.546168704 | 0.056755736 | 1.005039809 | 0.38799668 | 0.020787558 | 0.000000000 | 0.000000000 | 0.000000000 | 0.559072001 | 0.077225845 | AT1G34355 | 1.39303649 | 0.602924440 | 0.020787558 | 1.16199644 | 0.636297846 | PS1 |
| COL4 | 2.4169318 | 0.063200804 | 0.000000000 | 0.966848642 | 0.41908013 | 0.143167613 | 0.090663777 | 0.002508272 | 0.000000000 | 0.165613884 | 0.565848640 | AT5G24930 | 1.38592877 | 0.063200804 | 0.236339662 | 0.22881469 | 0.731462524 | COL4 |
| AT4G00940 | 2.3993025 | 0.000000000 | 0.000000000 | 0.203935552 | 1.04918249 | 0.005688667 | 0.035019085 | 1.105476677 | 0.000000000 | 0.000000000 | 0.000000000 | AT4G00940 | 1.25311804 | 0.000000000 | 1.146184429 | 0.00000000 | 0.000000000 | AT4G00940 |
| SUVR2 | 2.3134711 | 0.325030777 | 0.000000000 | 0.703323606 | 0.50964237 | 0.120001232 | 0.012475395 | 0.000000000 | 0.035791555 | 0.488670060 | 0.118536062 | AT5G43990 | 1.21296597 | 0.325030777 | 0.168268182 | 0.81370084 | 0.607206122 | SUVR2 |
| WRKY69 | 1.7522534 | 0.040652356 | 0.258101605 | 0.870534238 | 0.13749881 | 0.000000000 | 0.000000000 | 0.000000000 | 0.004497468 | 0.047418217 | 0.393550683 | AT3G58710 | 1.00803305 | 0.298753961 | 0.004497468 | 0.34617218 | 0.440968900 | WRKY69 |
| ZFN1 | 1.9539416 | 0.038933391 | 0.000000000 | 0.727648297 | 0.26632704 | 0.068901110 | 0.064464235 | 0.000000000 | 0.048401262 | 0.254359319 | 0.484906984 | AT3G02830 | 0.99397534 | 0.038933391 | 0.181766607 | 0.29329271 | 0.739266304 | ZFN1 |
| LCL1 | 1.7329580 | 0.019018672 | 0.000000000 | 0.303982413 | 0.60939017 | 0.232686240 | 0.341514227 | 0.041771769 | 0.069309790 | 0.000000000 | 0.115284710 | AT5G02840 | 0.91337258 | 0.019018672 | 0.685282026 | 0.01901867 | 0.115284710 | LCL1 |
| 3xHMG-box1 | 1.5450654 | 0.196338140 | 0.111861405 | 0.484529348 | 0.42847205 | 0.111876888 | 0.000000000 | 0.000000000 | 0.000000000 | 0.171555371 | 0.040432152 | AT4G11080 | 0.91300140 | 0.308199545 | 0.111876888 | 0.47975492 | 0.211987524 | 3xHMG-box1 |
| bZIP52 | 1.6245433 | 0.046008259 | 0.015014407 | 0.432320147 | 0.47774401 | 0.101767317 | 0.107019651 | 0.035400939 | 0.181669729 | 0.161749449 | 0.065849407 | AT1G06850 | 0.91006416 | 0.061022666 | 0.425857636 | 0.22277212 | 0.227598857 | bZIP52 |
| APRR2 | 1.7714481 | 0.000000000 | 0.000000000 | 0.485789146 | 0.41584802 | 0.102986446 | 0.188330026 | 0.000000000 | 0.535460274 | 0.000000000 | 0.043034202 | AT4G18020 | 0.90163716 | 0.000000000 | 0.826776745 | 0.00000000 | 0.043034202 | APRR2 |
| AT5G58900 | 1.3106062 | 0.051104408 | 0.110660095 | 0.597992303 | 0.22140808 | 0.000000000 | 0.007418725 | 0.007524815 | 0.249202773 | 0.016609935 | 0.048685091 | AT5G58900 | 0.81940038 | 0.161764502 | 0.264146314 | 0.17837444 | 0.065295026 | AT5G58900 |
| AT5G41920 | 1.3986689 | 0.000000000 | 0.000000000 | 0.109305439 | 0.63710435 | 0.652259084 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G41920 | 0.74640979 | 0.000000000 | 0.652259084 | 0.00000000 | 0.000000000 | AT5G41920 |
| AT5G58620 | 1.4402432 | 0.086608813 | 0.043989938 | 0.043670939 | 0.70041497 | 0.250150241 | 0.263850678 | 0.000000000 | 0.041948843 | 0.009608780 | 0.000000000 | AT5G58620 | 0.74408591 | 0.130598751 | 0.555949762 | 0.14020753 | 0.009608780 | AT5G58620 |
| AT1G16640 | 1.3064148 | 0.356329074 | 0.121084627 | 0.325830297 | 0.34747815 | 0.087930857 | 0.000000000 | 0.000000000 | 0.000000000 | 0.067761787 | 0.000000000 | AT1G16640 | 0.67330844 | 0.477413701 | 0.087930857 | 0.54517549 | 0.067761787 | AT1G16640 |
| AT3G61180 | 1.1727461 | 0.036857537 | 0.081297090 | 0.351443250 | 0.26853951 | 0.093960844 | 0.204021898 | 0.061583289 | 0.068726565 | 0.000000000 | 0.006316118 | AT3G61180 | 0.61998276 | 0.118154627 | 0.428292596 | 0.11815463 | 0.006316118 | AT3G61180 |
| GATA27 | 1.0010143 | 0.013811893 | 0.110196189 | 0.239503268 | 0.38018587 | 0.042672891 | 0.119367312 | 0.012574383 | 0.067724536 | 0.000000000 | 0.014977929 | AT5G47140 | 0.61968914 | 0.124008082 | 0.242339122 | 0.12400808 | 0.014977929 | GATA27 |
| AT5G23930 | 1.1554572 | 0.341155309 | 0.000000000 | 0.217370051 | 0.40154208 | 0.096015492 | 0.000000000 | 0.000000000 | 0.000000000 | 0.099374294 | 0.000000000 | AT5G23930 | 0.61891213 | 0.341155309 | 0.096015492 | 0.44052960 | 0.099374294 | AT5G23930 |
| ETR2 | 0.8810476 | 0.025868306 | 0.000000000 | 0.412857161 | 0.19745438 | 0.000000000 | 0.007418725 | 0.000000000 | 0.000000000 | 0.000000000 | 0.237449024 | AT3G23150 | 0.61031154 | 0.025868306 | 0.007418725 | 0.02586831 | 0.237449024 | ETR2 |
| MYB14 | 1.1598497 | 0.080736391 | 0.000000000 | 0.434523451 | 0.16433452 | 0.112716303 | 0.167740974 | 0.100861831 | 0.000000000 | 0.000000000 | 0.098936221 | AT2G31180 | 0.59885797 | 0.080736391 | 0.381319108 | 0.08073639 | 0.098936221 | MYB14 |
| AT2G18850 | 1.0043199 | 0.265798096 | 0.049790986 | 0.440368143 | 0.13386258 | 0.022468984 | 0.008297122 | 0.007557840 | 0.000000000 | 0.034516230 | 0.041659886 | AT2G18850 | 0.57423072 | 0.315589081 | 0.038323945 | 0.35010531 | 0.076176116 | AT2G18850 |
| AT5G66270 | 1.0381664 | 0.253435414 | 0.089538398 | 0.223487935 | 0.30412381 | 0.066242104 | 0.000000000 | 0.000000000 | 0.000000000 | 0.069823998 | 0.031514723 | AT5G66270 | 0.52761175 | 0.342973812 | 0.066242104 | 0.41279781 | 0.101338721 | AT5G66270 |
| MYB70 | 0.6756527 | 0.004093299 | 0.010766070 | 0.118862041 | 0.31425952 | 0.070259808 | 0.006930481 | 0.000000000 | 0.047744553 | 0.033848569 | 0.068888390 | AT2G23290 | 0.43312156 | 0.014859369 | 0.124934843 | 0.04870794 | 0.102736959 | MYB70 |
| ARR9 | 0.7985496 | 0.029599649 | 0.047370685 | 0.096343680 | 0.32658562 | 0.036901919 | 0.101063431 | 0.111231055 | 0.023815852 | 0.000000000 | 0.025637763 | AT3G57040 | 0.42292930 | 0.076970334 | 0.273012257 | 0.07697033 | 0.025637763 | ARR9 |
| ING1 | 0.6800806 | 0.009851456 | 0.024933884 | 0.024281286 | 0.32972088 | 0.036606105 | 0.048414902 | 0.016287255 | 0.123860308 | 0.007576104 | 0.058548459 | AT3G24010 | 0.35400216 | 0.034785341 | 0.225168570 | 0.04236145 | 0.066124563 | ING1 |
| AT5G58280 | 0.6589519 | 0.095722637 | 0.000000000 | 0.246624049 | 0.09621251 | 0.023448229 | 0.000000000 | 0.000000000 | 0.000000000 | 0.128355047 | 0.068589410 | AT5G58280 | 0.34283656 | 0.095722637 | 0.023448229 | 0.22407768 | 0.196944457 | AT5G58280 |
| AHBP-1B | 0.5457062 | 0.000000000 | 0.014891257 | 0.109522503 | 0.19195473 | 0.048301174 | 0.025170840 | 0.011336759 | 0.070534984 | 0.025764625 | 0.048229351 | AT5G06950 | 0.30147723 | 0.014891257 | 0.155343757 | 0.04065588 | 0.073993975 | AHBP-1B |
| ZFN3 | 0.4990681 | 0.040070362 | 0.120583045 | 0.129386842 | 0.16132178 | 0.000000000 | 0.000000000 | 0.000000000 | 0.038908574 | 0.000000000 | 0.008797508 | AT5G16540 | 0.29070862 | 0.160653407 | 0.038908574 | 0.16065341 | 0.008797508 | ZFN3 |
| AT5G43530 | 0.4767440 | 0.080377787 | 0.078633741 | 0.108588739 | 0.15390481 | 0.055238945 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT5G43530 | 0.26249355 | 0.159011527 | 0.055238945 | 0.15901153 | 0.000000000 | AT5G43530 |
| EPR1 | 0.4293309 | 0.004093299 | 0.000000000 | 0.126930325 | 0.13466900 | 0.000000000 | 0.010649917 | 0.080085697 | 0.020145733 | 0.024993840 | 0.027763127 | AT1G18330 | 0.26159932 | 0.004093299 | 0.110881346 | 0.02908714 | 0.052756966 | EPR1 |
| AGL65 | 0.4719325 | 0.056449854 | 0.000000000 | 0.161679530 | 0.09215518 | 0.037786153 | 0.005392758 | 0.000000000 | 0.000000000 | 0.078036838 | 0.040432152 | AT1G18750 | 0.25383471 | 0.056449854 | 0.043178911 | 0.13448669 | 0.118468990 | AGL65 |
| AT5G07810 | 0.3887479 | 0.035257420 | 0.025398776 | 0.148957880 | 0.09997634 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.049240538 | 0.029916967 | AT5G07810 | 0.24893422 | 0.060656195 | 0.000000000 | 0.10989673 | 0.079157505 | AT5G07810 |
| NSI | 0.4222833 | 0.032764253 | 0.068238176 | 0.068522550 | 0.14313237 | 0.055236231 | 0.018131918 | 0.004983519 | 0.022420414 | 0.000000000 | 0.008853830 | AT1G32070 | 0.21165492 | 0.101002429 | 0.100772083 | 0.10100243 | 0.008853830 | NSI |
| AT2G46735 | 0.3031413 | 0.028737266 | 0.038328706 | 0.080708960 | 0.07751234 | 0.000000000 | 0.044635983 | 0.002508272 | 0.015654122 | 0.000000000 | 0.015055632 | AT2G46735 | 0.15822130 | 0.067065972 | 0.062798376 | 0.06706597 | 0.015055632 | AT2G46735 |
| AT5G05130 | 0.1370665 | 0.006619989 | 0.000000000 | 0.041166101 | 0.05140327 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.017414117 | 0.020462979 | AT5G05130 | 0.09256937 | 0.006619989 | 0.000000000 | 0.02403411 | 0.037877096 | AT5G05130 |
| AT5G13920 | 0.1258854 | 0.000000000 | 0.015803819 | 0.008117677 | 0.05786379 | 0.017455709 | 0.017749304 | 0.000000000 | 0.008895096 | 0.000000000 | 0.000000000 | AT5G13920 | 0.06598147 | 0.015803819 | 0.044100108 | 0.01580382 | 0.000000000 | AT5G13920 |
| AT5G47790 | 0.1216455 | 0.000000000 | 0.009187834 | 0.008311856 | 0.05532825 | 0.000000000 | 0.007418725 | 0.008795463 | 0.025247070 | 0.003577863 | 0.003778406 | AT5G47790 | 0.06364010 | 0.009187834 | 0.041461258 | 0.01276570 | 0.007356270 | AT5G47790 |
| AT2G17150 | 0.1140957 | 0.000000000 | 0.000000000 | 0.008311856 | 0.05229974 | 0.000000000 | 0.016450647 | 0.000000000 | 0.006095925 | 0.000000000 | 0.030937564 | AT2G17150 | 0.06061159 | 0.000000000 | 0.022546572 | 0.00000000 | 0.030937564 | AT2G17150 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(ground_rank[1:10,], aes(x=reorder(GeneName, ground, decreasing = FALSE), y=ground)) + geom_point(size=4)+
labs(title="Ground Tissue-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(ground_rank,"Ground_Tissue_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- ground_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Ground Tissue ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
epi_rank <- bc_rank[which(bc_rank$epi*2 > bc_rank$all),]%>% arrange(desc(epi))
epi_rank <- epi_rank[-c(match(rownames(atri_rank), rownames(epi_rank)),match(rownames(tri_rank), rownames(epi_rank))),]
epi_rank$GeneName <- rownames(epi_rank)
epi_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | ground | epi | stele | epilrc | rc | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | |
| WRKY75 | 14.27247625 | 4.50121971 | 6.35682293 | 0.105330391 | 0.020802243 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.562987445 | 2.725313541 | AT5G13080 | 0.126132634 | 10.85804263 | 0.000000000 | 11.42103008 | 3.288300987 | WRKY75 |
| KDR | 11.62635997 | 5.16954066 | 4.61693369 | 0.687132713 | 0.421165730 | 0.122605397 | 0.000000000 | 0.000000000 | 0.00000000 | 0.467248858 | 0.141732932 | AT1G26945 | 1.108298444 | 9.78647434 | 0.122605397 | 10.25372320 | 0.608981789 | KDR |
| TGA10 | 11.88448968 | 4.95436167 | 4.44299660 | 1.568650672 | 0.855081570 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.063399162 | 0.000000000 | AT5G06839 | 2.423732242 | 9.39735827 | 0.000000000 | 9.46075743 | 0.063399162 | TGA10 |
| ATS | 16.50726004 | 5.44112099 | 3.30585225 | 0.968613101 | 0.707613234 | 0.051316603 | 0.000000000 | 0.000000000 | 0.00000000 | 5.946192427 | 0.086551437 | AT5G42630 | 1.676226335 | 8.74697324 | 0.051316603 | 14.69316566 | 6.032743865 | ATS |
| ATMYC1 | 9.78145051 | 3.77655716 | 4.62113827 | 0.678339208 | 0.609503007 | 0.095912867 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT4G00480 | 1.287842216 | 8.39769543 | 0.095912867 | 8.39769543 | 0.000000000 | ATMYC1 |
| ATHB13 | 12.94066661 | 3.43823012 | 4.68668673 | 1.275819260 | 1.039918586 | 1.305370636 | 0.284257457 | 0.000000000 | 0.11530623 | 0.742912093 | 0.052165503 | AT1G69780 | 2.315737846 | 8.12491684 | 1.704934322 | 8.86782894 | 0.795077596 | ATHB13 |
| ARR5 | 8.89376453 | 3.90153218 | 3.60543610 | 0.323971285 | 0.220153526 | 0.004604770 | 0.036677828 | 0.028683106 | 0.04366444 | 0.315386196 | 0.413655090 | AT3G48100 | 0.544124811 | 7.50696828 | 0.113630146 | 7.82235448 | 0.729041287 | ARR5 |
| EGL3 | 9.21190572 | 3.31146732 | 2.93164385 | 1.616857995 | 1.213590291 | 0.138346265 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT1G63650 | 2.830448286 | 6.24311117 | 0.138346265 | 6.24311117 | 0.000000000 | EGL3 |
| RSL1 | 7.02070379 | 2.79503956 | 3.39167865 | 0.391179276 | 0.442806304 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT5G37800 | 0.833985580 | 6.18671821 | 0.000000000 | 6.18671821 | 0.000000000 | RSL1 |
| TRY | 9.06259414 | 4.42583642 | 1.73861316 | 1.326472988 | 1.187753102 | 0.065521148 | 0.000000000 | 0.000000000 | 0.02658114 | 0.291816191 | 0.000000000 | AT5G53200 | 2.514226090 | 6.16444958 | 0.092102284 | 6.45626577 | 0.291816191 | TRY |
| WRKY65 | 7.76971222 | 2.97579985 | 2.87049627 | 0.065232345 | 0.198280979 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 1.174474140 | 0.485428646 | AT1G29280 | 0.263513325 | 5.84629611 | 0.000000000 | 7.02077025 | 1.659902786 | WRKY65 |
| NFL | 8.51771460 | 2.69458888 | 2.66075182 | 1.211807252 | 0.957362456 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.766809048 | 0.226395146 | AT5G65640 | 2.169169709 | 5.35534070 | 0.000000000 | 6.12214975 | 0.993204194 | NFL |
| WRKY31 | 4.08517147 | 1.79205116 | 1.93379457 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.113247738 | 0.246078001 | AT4G22070 | 0.000000000 | 3.72584574 | 0.000000000 | 3.83909347 | 0.359325739 | WRKY31 |
| ARR4 | 6.72900087 | 2.21785353 | 1.49870609 | 0.352242975 | 0.259826637 | 0.032473533 | 0.093496702 | 0.902702934 | 0.36938618 | 0.588931939 | 0.413380355 | AT1G10470 | 0.612069613 | 3.71655962 | 1.398059346 | 4.30549156 | 1.002312294 | ARR4 |
| BNQ3 | 5.05983326 | 2.39743980 | 0.92866023 | 0.007722008 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 1.714071366 | 0.011939866 | AT3G47710 | 0.007722008 | 3.32610002 | 0.000000000 | 5.04017139 | 1.726011231 | BNQ3 |
| tny | 5.94109200 | 0.07049984 | 2.92972090 | 2.845054038 | 0.009767087 | 0.003045749 | 0.083004383 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT5G25810 | 2.854821125 | 3.00022074 | 0.086050132 | 3.00022074 | 0.000000000 | tny |
| AT3G14740 | 4.63360687 | 1.48628662 | 1.02910395 | 0.052439006 | 0.080853310 | 0.857512895 | 0.234059451 | 0.311910070 | 0.15857334 | 0.405268899 | 0.017599319 | AT3G14740 | 0.133292317 | 2.51539058 | 1.562055760 | 2.92065947 | 0.422868218 | AT3G14740 |
| AT5G44260 | 4.24918637 | 0.51514067 | 1.90034095 | 0.363876159 | 0.544155781 | 0.074447267 | 0.000000000 | 0.000000000 | 0.00000000 | 0.509355564 | 0.341869975 | AT5G44260 | 0.908031940 | 2.41548162 | 0.074447267 | 2.92483718 | 0.851225540 | AT5G44260 |
| WRI1 | 3.72151672 | 1.71959721 | 0.56962058 | 0.258343579 | 0.186074488 | 0.088291335 | 0.000000000 | 0.000000000 | 0.00000000 | 0.812360475 | 0.087229041 | AT3G54320 | 0.444418067 | 2.28921780 | 0.088291335 | 3.10157827 | 0.899589516 | WRI1 |
| AT4G26810 | 3.39210973 | 1.24137412 | 0.94041031 | 0.222932437 | 0.261870227 | 0.495560627 | 0.224601616 | 0.000000000 | 0.00000000 | 0.005360395 | 0.000000000 | AT4G26810 | 0.484802664 | 2.18178443 | 0.720162242 | 2.18714482 | 0.005360395 | AT4G26810 |
| NF-YC13 | 3.69251878 | 1.30516262 | 0.84404440 | 0.387994507 | 0.699191452 | 0.002982303 | 0.000000000 | 0.333651367 | 0.00000000 | 0.119492121 | 0.000000000 | AT5G43250 | 1.087185959 | 2.14920703 | 0.336633670 | 2.26869915 | 0.119492121 | NF-YC13 |
| OFP13 | 2.83417196 | 0.77262982 | 1.23976071 | 0.387420971 | 0.256171992 | 0.008669323 | 0.003185921 | 0.000000000 | 0.00000000 | 0.093051719 | 0.073281496 | AT5G04820 | 0.643592963 | 2.01239053 | 0.011855244 | 2.10544225 | 0.166333215 | OFP13 |
| HDG7 | 3.31341935 | 1.57034339 | 0.43963925 | 0.530950184 | 0.407675480 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.325434691 | 0.039376358 | AT5G52170 | 0.938625664 | 2.00998263 | 0.000000000 | 2.33541732 | 0.364811049 | HDG7 |
| HRS1 | 2.75985065 | 1.31214046 | 0.59487847 | 0.298884996 | 0.519438376 | 0.027089623 | 0.007418725 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT1G13300 | 0.818323372 | 1.90701893 | 0.034508348 | 1.90701893 | 0.000000000 | HRS1 |
| HMGB2 | 2.75746694 | 0.62455463 | 1.07055053 | 0.175173093 | 0.244648860 | 0.223163133 | 0.165502300 | 0.020099199 | 0.19185287 | 0.008576734 | 0.033345588 | AT1G20693 | 0.419821953 | 1.69510516 | 0.600617505 | 1.70368189 | 0.041922322 | HMGB2 |
| AT5G42700 | 2.66806247 | 1.14692762 | 0.23198585 | 0.400151095 | 0.362753222 | 0.222492104 | 0.000000000 | 0.243623750 | 0.00000000 | 0.060128828 | 0.000000000 | AT5G42700 | 0.762904317 | 1.37891347 | 0.466115854 | 1.43904229 | 0.060128828 | AT5G42700 |
| MED6 | 1.44791533 | 0.47208033 | 0.53292250 | 0.024353030 | 0.187227487 | 0.076984211 | 0.010724510 | 0.020132223 | 0.04896930 | 0.041097619 | 0.033424122 | AT3G21350 | 0.211580518 | 1.00500283 | 0.156810246 | 1.04610045 | 0.074521741 | MED6 |
| ORC1B | 1.48364884 | 0.53621302 | 0.41805620 | 0.000000000 | 0.052070705 | 0.159463448 | 0.012356546 | 0.262605753 | 0.00000000 | 0.042883156 | 0.000000000 | AT4G12620 | 0.052070705 | 0.95426923 | 0.434425747 | 0.99715239 | 0.042883156 | ORC1B |
| LOL2 | 1.19935231 | 0.39396708 | 0.48163750 | 0.032759566 | 0.000000000 | 0.046119087 | 0.020831941 | 0.006320216 | 0.01068484 | 0.159327474 | 0.047704601 | AT4G21610 | 0.032759566 | 0.87560458 | 0.083956084 | 1.03493206 | 0.207032076 | LOL2 |
| HFR1 | 1.49598207 | 0.38654756 | 0.43671310 | 0.488623933 | 0.184097466 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT1G02340 | 0.672721399 | 0.82326067 | 0.000000000 | 0.82326067 | 0.000000000 | HFR1 |
| HDG1 | 1.23260977 | 0.46529083 | 0.24272326 | 0.080984194 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.390817231 | 0.052794262 | AT3G61150 | 0.080984194 | 0.70801408 | 0.000000000 | 1.09883131 | 0.443611493 | HDG1 |
| MBD6 | 0.95978369 | 0.28416110 | 0.42150179 | 0.035529649 | 0.008604207 | 0.117048819 | 0.005302323 | 0.026321159 | 0.01059339 | 0.044948472 | 0.005772775 | AT5G59380 | 0.044133855 | 0.70566289 | 0.159265694 | 0.75061136 | 0.050721247 | MBD6 |
| NF-YC10 | 1.13370071 | 0.25995401 | 0.43410473 | 0.100555977 | 0.193202483 | 0.020012672 | 0.003185921 | 0.000000000 | 0.01241380 | 0.036939252 | 0.073331868 | AT1G07980 | 0.293758460 | 0.69405874 | 0.035612395 | 0.73099799 | 0.110271120 | NF-YC10 |
| RSZ22a | 1.18417349 | 0.41119117 | 0.27535727 | 0.000000000 | 0.055363523 | 0.100303568 | 0.022224698 | 0.016386327 | 0.11485350 | 0.158637357 | 0.029856069 | AT2G24590 | 0.055363523 | 0.68654844 | 0.253768098 | 0.84518580 | 0.188493427 | RSZ22a |
| WRKY3 | 0.93124326 | 0.31051817 | 0.24381423 | 0.000000000 | 0.002868069 | 0.009137246 | 0.027389773 | 0.000000000 | 0.04343970 | 0.131535984 | 0.162540092 | AT2G03340 | 0.002868069 | 0.55433239 | 0.079966716 | 0.68586838 | 0.294076077 | WRKY3 |
| AT5G66770 | 1.09068944 | 0.45600043 | 0.09499634 | 0.135519279 | 0.074234484 | 0.007721640 | 0.012415970 | 0.037543358 | 0.01338920 | 0.189002563 | 0.069866180 | AT5G66770 | 0.209753764 | 0.55099677 | 0.071070168 | 0.73999933 | 0.258868743 | AT5G66770 |
| AT3G57480 | 0.81065314 | 0.20361446 | 0.28739796 | 0.006228522 | 0.034553874 | 0.002863808 | 0.006360524 | 0.126151523 | 0.00000000 | 0.082666118 | 0.060816364 | AT3G57480 | 0.040782397 | 0.49101241 | 0.135375855 | 0.57367853 | 0.143482482 | AT3G57480 |
| PUX2 | 0.71372439 | 0.28674622 | 0.17953620 | 0.035151157 | 0.105239453 | 0.000000000 | 0.027878112 | 0.006320216 | 0.01658114 | 0.005966671 | 0.050305224 | AT2G01650 | 0.140390610 | 0.46628242 | 0.050779464 | 0.47224909 | 0.056271895 | PUX2 |
| NPR1 | 0.72784235 | 0.23596400 | 0.15667550 | 0.049562669 | 0.057509664 | 0.004849074 | 0.006904364 | 0.000000000 | 0.00000000 | 0.077267382 | 0.139109693 | AT1G64280 | 0.107072333 | 0.39263950 | 0.011753438 | 0.46990688 | 0.216377075 | NPR1 |
| AT2G01060 | 0.60397090 | 0.09311377 | 0.29945681 | 0.028485217 | 0.055838837 | 0.020628326 | 0.000000000 | 0.002508272 | 0.02401195 | 0.042542271 | 0.037385446 | AT2G01060 | 0.084324054 | 0.39257058 | 0.047148546 | 0.43511285 | 0.079927717 | AT2G01060 |
| AT1G76110 | 0.52155936 | 0.14219343 | 0.22133878 | 0.059593820 | 0.055629424 | 0.037292296 | 0.005511606 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT1G76110 | 0.115223244 | 0.36353221 | 0.042803902 | 0.36353221 | 0.000000000 | AT1G76110 |
| ATMAK3 | 0.56549872 | 0.20148093 | 0.14449258 | 0.000000000 | 0.033498370 | 0.063714866 | 0.029090761 | 0.026320342 | 0.02126596 | 0.040454391 | 0.005180522 | AT2G38130 | 0.033498370 | 0.34597351 | 0.140391929 | 0.38642790 | 0.045634913 | ATMAK3 |
| CHR8 | 0.45170578 | 0.12096937 | 0.19871424 | 0.000000000 | 0.025413486 | 0.000000000 | 0.032010385 | 0.000000000 | 0.02654383 | 0.000000000 | 0.048054472 | AT2G18760 | 0.025413486 | 0.31968361 | 0.058554211 | 0.31968361 | 0.048054472 | CHR8 |
| AT5G28300 | 0.44283743 | 0.18600653 | 0.12138746 | 0.086338384 | 0.004780115 | 0.000000000 | 0.000000000 | 0.000000000 | 0.02674835 | 0.000000000 | 0.017576592 | AT5G28300 | 0.091118498 | 0.30739399 | 0.026748349 | 0.30739399 | 0.017576592 | AT5G28300 |
| WRKY54 | 0.36001476 | 0.14209582 | 0.08107857 | 0.000000000 | 0.000000000 | 0.000000000 | 0.019201486 | 0.000000000 | 0.00000000 | 0.112753568 | 0.004885314 | AT2G40750 | 0.000000000 | 0.22317439 | 0.019201486 | 0.33592796 | 0.117638881 | WRKY54 |
| EMB2219 | 0.33585476 | 0.12743751 | 0.05277167 | 0.022064379 | 0.040583082 | 0.025158402 | 0.009630455 | 0.000000000 | 0.00000000 | 0.036432218 | 0.021777039 | AT2G21710 | 0.062647461 | 0.18020918 | 0.034788857 | 0.21664140 | 0.058209257 | EMB2219 |
| AT2G37000 | 0.17297214 | 0.05694063 | 0.08066012 | 0.031252544 | 0.000000000 | 0.000000000 | 0.004118849 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT2G37000 | 0.031252544 | 0.13760075 | 0.004118849 | 0.13760075 | 0.000000000 | AT2G37000 |
| FRF1 | 0.19864460 | 0.04216337 | 0.08087802 | 0.005836971 | 0.028956831 | 0.000000000 | 0.026028442 | 0.000000000 | 0.01478097 | 0.000000000 | 0.000000000 | AT3G59470 | 0.034793803 | 0.12304139 | 0.040809407 | 0.12304139 | 0.000000000 | FRF1 |
| AT3G51180 | 0.09952575 | 0.04051087 | 0.02509337 | 0.000000000 | 0.028619193 | 0.000000000 | 0.005302323 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | AT3G51180 | 0.028619193 | 0.06560423 | 0.005302323 | 0.06560423 | 0.000000000 | AT3G51180 |
| AT1G61960 | 0.05563907 | 0.02294639 | 0.02089916 | 0.000000000 | 0.002868069 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.008925457 | 0.000000000 | AT1G61960 | 0.002868069 | 0.04384555 | 0.000000000 | 0.05277100 | 0.008925457 | AT1G61960 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(epi_rank[1:10,], aes(x=reorder(GeneName, epi, decreasing = FALSE), y=epi)) + geom_point(size=4)+
labs(title="Epidermis-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(epi_rank,"Epidermis_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- epi_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Epidermis ", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
epilrc_rank <- bc_rank[which(bc_rank$epilrc*2 > bc_rank$all),]%>% arrange(desc(epilrc))
epilrc_rank <- epilrc_rank[-c(match(rownames(atri_rank), rownames(epilrc_rank)),match(rownames(tri_rank), rownames(epilrc_rank)),match(rownames(lrc_rank), rownames(epilrc_rank))),]
epilrc_rank$GeneName <- rownames(epilrc_rank)
epilrc_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | ground | epi | stele | epilrc | rc | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | |
| GATA2 | 33.122726 | 6.623792 | 6.596556930 | 2.4662178 | 2.051664424 | 0.80375905 | 0.038818942 | 0.094062436 | 0.155952926 | 12.10350859 | 2.18839297 | AT2G45050 | 4.5178822 | 13.220349 | 1.092593358 | 25.323857 | 14.29190157 | GATA2 |
| NAI1 | 26.293062 | 4.531465 | 2.427442200 | 0.4453633 | 0.205157772 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 10.31475737 | 8.36887560 | AT2G22770 | 0.6505211 | 6.958907 | 0.000000000 | 17.273665 | 18.68363298 | NAI1 |
| CRF3 | 23.156426 | 3.728132 | 2.509432523 | 1.5634632 | 1.455509716 | 0.22797244 | 0.046967234 | 0.000000000 | 0.007808814 | 9.41462626 | 4.20251415 | AT5G53290 | 3.0189729 | 6.237564 | 0.282748493 | 15.652190 | 13.61714041 | CRF3 |
| ATS | 16.507260 | 5.441121 | 3.305852246 | 0.9686131 | 0.707613234 | 0.05131660 | 0.000000000 | 0.000000000 | 0.000000000 | 5.94619243 | 0.08655144 | AT5G42630 | 1.6762263 | 8.746973 | 0.051316603 | 14.693166 | 6.03274386 | ATS |
| WRKY9 | 16.059040 | 3.419059 | 3.623664192 | 0.0000000 | 0.000000000 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 7.33266559 | 1.68365192 | AT1G68150 | 0.0000000 | 7.042723 | 0.000000000 | 14.375388 | 9.01631751 | WRKY9 |
| WER | 21.502304 | 4.805167 | 3.023849655 | 2.2988231 | 1.929804951 | 1.60818052 | 0.000000000 | 0.000000000 | 0.000000000 | 6.47458657 | 1.36189276 | AT5G14750 | 4.2286280 | 7.829016 | 1.608180520 | 14.303603 | 7.83647933 | WER |
| BRON | 21.210029 | 4.113443 | 1.541404242 | 1.7786247 | 0.797459038 | 0.02949052 | 0.000000000 | 0.000000000 | 0.000000000 | 8.37774914 | 4.57185874 | AT1G75710 | 2.5760837 | 5.654847 | 0.029490525 | 14.032596 | 12.94960788 | BRON |
| CRF2 | 26.776206 | 4.253729 | 2.624377101 | 2.0929756 | 1.946945888 | 2.86595170 | 0.227652705 | 0.076617017 | 1.680974990 | 7.01682963 | 3.99015150 | AT4G23750 | 4.0399215 | 6.878107 | 4.851196406 | 13.894936 | 11.00698114 | CRF2 |
| BT2 | 21.465456 | 3.193818 | 1.318831580 | 0.1865704 | 0.008604207 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 8.80460777 | 7.95302395 | AT3G48360 | 0.1951746 | 4.512650 | 0.000000000 | 13.317258 | 16.75763172 | BT2 |
| PLT1 | 23.975143 | 3.940608 | 0.000000000 | 2.0095313 | 1.492057686 | 0.05699842 | 0.000000000 | 0.000000000 | 0.000000000 | 9.14800761 | 7.32793997 | AT3G20840 | 3.5015890 | 3.940608 | 0.056998421 | 13.088616 | 16.47594759 | PLT1 |
| AT1G36060 | 19.317669 | 3.288870 | 0.911066727 | 0.4154557 | 0.417050853 | 0.01438478 | 0.000000000 | 0.000000000 | 0.000000000 | 7.43126331 | 6.83957810 | AT1G36060 | 0.8325066 | 4.199936 | 0.014384784 | 11.631200 | 14.27084142 | AT1G36060 |
| WRKY75 | 14.272476 | 4.501220 | 6.356822928 | 0.1053304 | 0.020802243 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.56298745 | 2.72531354 | AT5G13080 | 0.1261326 | 10.858043 | 0.000000000 | 11.421030 | 3.28830099 | WRKY75 |
| GATA4 | 19.762788 | 5.005152 | 3.160243703 | 2.9003810 | 3.408120604 | 0.22564199 | 0.000000000 | 0.188124872 | 0.033494724 | 2.96550233 | 1.87612624 | AT3G60530 | 6.3085016 | 8.165396 | 0.447261590 | 11.130898 | 4.84162856 | GATA4 |
| TMO7 | 20.540646 | 5.343586 | 2.778498293 | 4.3047024 | 1.404510625 | 0.69068801 | 0.000000000 | 0.000000000 | 0.007790552 | 2.93997637 | 3.07089432 | AT1G74500 | 5.7092130 | 8.122084 | 0.698478562 | 11.062060 | 6.01087069 | TMO7 |
| SMB | 18.647620 | 3.795156 | 0.154934264 | 1.3885615 | 0.208595675 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 6.95364674 | 6.14672573 | AT1G79580 | 1.5971572 | 3.950090 | 0.000000000 | 10.903737 | 13.10037247 | SMB |
| WRKY17 | 15.090675 | 3.305227 | 1.357150829 | 1.1777238 | 0.737343969 | 0.32690649 | 0.029931039 | 0.694344583 | 0.261731502 | 6.01333696 | 1.18697873 | AT2G24570 | 1.9150678 | 4.662378 | 1.312913611 | 10.675715 | 7.20031569 | WRKY17 |
| AT1G26680 | 17.564236 | 2.110786 | 0.000000000 | 1.4957776 | 0.073110164 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 8.56440431 | 5.32015736 | AT1G26680 | 1.5688878 | 2.110786 | 0.000000000 | 10.675190 | 13.88456168 | AT1G26680 |
| IAA1 | 12.462540 | 3.713086 | 1.531036993 | 0.3683942 | 0.026348207 | 0.00000000 | 0.000000000 | 0.007524815 | 0.000000000 | 5.30853878 | 1.50761152 | AT4G14560 | 0.3947424 | 5.244123 | 0.007524815 | 10.552661 | 6.81615030 | IAA1 |
| NAC094 | 17.625583 | 4.047506 | 0.006587797 | 1.7146054 | 1.039673292 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 6.45049619 | 4.36671461 | AT5G39820 | 2.7542787 | 4.054093 | 0.000000000 | 10.504590 | 10.81721080 | NAC094 |
| LBD15 | 19.199671 | 1.994126 | 0.583368907 | 0.1850179 | 0.012611943 | 0.00000000 | 0.000000000 | 2.574826946 | 0.000000000 | 7.82336644 | 6.02635266 | AT2G40470 | 0.1976298 | 2.577495 | 2.574826946 | 10.400861 | 13.84971910 | LBD15 |
| ERF9 | 16.487505 | 3.556433 | 0.370499429 | 1.4782014 | 0.526822244 | 1.40757652 | 0.007418725 | 1.389018316 | 0.000000000 | 6.37419496 | 1.37734056 | AT5G44210 | 2.0050237 | 3.926933 | 2.804013560 | 10.301128 | 7.75153552 | ERF9 |
| KDR | 11.626360 | 5.169541 | 4.616933686 | 0.6871327 | 0.421165730 | 0.12260540 | 0.000000000 | 0.000000000 | 0.000000000 | 0.46724886 | 0.14173293 | AT1G26945 | 1.1082984 | 9.786474 | 0.122605397 | 10.253723 | 0.60898179 | KDR |
| ARF16 | 13.237412 | 2.336406 | 1.817921968 | 0.5725253 | 0.260294865 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 5.44063804 | 2.80962553 | AT4G30080 | 0.8328201 | 4.154328 | 0.000000000 | 9.594966 | 8.25026357 | ARF16 |
| TGA10 | 11.884490 | 4.954362 | 4.442996603 | 1.5686507 | 0.855081570 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.06339916 | 0.00000000 | AT5G06839 | 2.4237322 | 9.397358 | 0.000000000 | 9.460757 | 0.06339916 | TGA10 |
| FEZ | 15.332752 | 3.375534 | 0.000000000 | 1.8148960 | 0.697963324 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 5.64952955 | 3.79482909 | AT1G26870 | 2.5128593 | 3.375534 | 0.000000000 | 9.025063 | 9.44435864 | FEZ |
| ATHB13 | 12.940667 | 3.438230 | 4.686686725 | 1.2758193 | 1.039918586 | 1.30537064 | 0.284257457 | 0.000000000 | 0.115306229 | 0.74291209 | 0.05216550 | AT1G69780 | 2.3157378 | 8.124917 | 1.704934322 | 8.867829 | 0.79507760 | ATHB13 |
| RITF1 | 16.752082 | 3.595258 | 2.290070342 | 1.8809351 | 2.633114574 | 1.84999357 | 0.000000000 | 0.000000000 | 0.000000000 | 2.86415361 | 1.63855709 | AT2G12646 | 4.5140497 | 5.885328 | 1.849993567 | 8.749482 | 4.50271070 | RITF1 |
| ATMYC1 | 9.781451 | 3.776557 | 4.621138269 | 0.6783392 | 0.609503007 | 0.09591287 | 0.000000000 | 0.000000000 | 0.000000000 | 0.00000000 | 0.00000000 | AT4G00480 | 1.2878422 | 8.397695 | 0.095912867 | 8.397695 | 0.00000000 | ATMYC1 |
| GATA17L | 16.026613 | 3.317978 | 2.050499537 | 1.7886792 | 1.848639233 | 2.33675846 | 0.148609099 | 0.222851886 | 0.025486200 | 2.82295636 | 1.46415566 | AT4G16141 | 3.6373184 | 5.368477 | 2.733705643 | 8.191434 | 4.28711202 | GATA17L |
| AT1G22190 | 12.423250 | 3.142520 | 0.104379338 | 0.8610697 | 0.121072079 | 0.00000000 | 0.061920525 | 0.094488107 | 0.005574178 | 4.67688454 | 3.35534187 | AT1G22190 | 0.9821417 | 3.246899 | 0.161982810 | 7.923784 | 8.03222642 | AT1G22190 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| HSFA8 | 0.41967666 | 0.060946896 | 0.028177887 | 0.000000000 | 0.017208413 | 0.019038236 | 0.000000000 | 0.000000000 | 0.082472685 | 0.168664215 | 0.043168332 | AT1G67970 | 0.017208413 | 0.089124783 | 0.101510921 | 0.25778900 | 0.211832546 | HSFA8 |
| AT4G14490 | 0.48144152 | 0.097914758 | 0.062991755 | 0.021775520 | 0.065075118 | 0.118963797 | 0.010144816 | 0.008569680 | 0.006095925 | 0.089910146 | 0.000000000 | AT4G14490 | 0.086850638 | 0.160906513 | 0.143774218 | 0.25081666 | 0.089910146 | AT4G14490 |
| AT1G60700 | 0.40994951 | 0.182460085 | 0.007980554 | 0.034855645 | 0.000000000 | 0.017716305 | 0.000000000 | 0.072740257 | 0.020062073 | 0.059421663 | 0.014712932 | AT1G60700 | 0.034855645 | 0.190440639 | 0.110518635 | 0.24986230 | 0.074134594 | AT1G60700 |
| AT1G77250 | 0.42446752 | 0.032777583 | 0.073026501 | 0.016693775 | 0.026698833 | 0.002863808 | 0.006800194 | 0.000000000 | 0.027738283 | 0.140674630 | 0.097193912 | AT1G77250 | 0.043392609 | 0.105804084 | 0.037402286 | 0.24647871 | 0.237868542 | AT1G77250 |
| AT1G72030 | 0.36551917 | 0.073569283 | 0.000000000 | 0.021968092 | 0.000000000 | 0.048370026 | 0.009630455 | 0.000000000 | 0.000000000 | 0.161363129 | 0.050618187 | AT1G72030 | 0.021968092 | 0.073569283 | 0.058000481 | 0.23493241 | 0.211981316 | AT1G72030 |
| KAPP | 0.41819526 | 0.037603271 | 0.137870812 | 0.014134199 | 0.028488413 | 0.007540878 | 0.005302323 | 0.018861575 | 0.025266868 | 0.053232042 | 0.089894880 | AT5G19280 | 0.042622612 | 0.175474083 | 0.056971644 | 0.22870613 | 0.143126922 | KAPP |
| EMB2219 | 0.33585476 | 0.127437508 | 0.052771672 | 0.022064379 | 0.040583082 | 0.025158402 | 0.009630455 | 0.000000000 | 0.000000000 | 0.036432218 | 0.021777039 | AT2G21710 | 0.062647461 | 0.180209180 | 0.034788857 | 0.21664140 | 0.058209257 | EMB2219 |
| VFP5 | 0.37607797 | 0.108112348 | 0.006079414 | 0.041069815 | 0.000000000 | 0.018602837 | 0.018103794 | 0.000000000 | 0.028074780 | 0.101070713 | 0.054964265 | AT5G05550 | 0.041069815 | 0.114191762 | 0.064781412 | 0.21526248 | 0.156034979 | VFP5 |
| AT3G53440 | 0.29755250 | 0.008732049 | 0.067282196 | 0.019005436 | 0.035705883 | 0.000000000 | 0.002127720 | 0.000000000 | 0.000000000 | 0.130320835 | 0.034378383 | AT3G53440 | 0.054711320 | 0.076014245 | 0.002127720 | 0.20633508 | 0.164699218 | AT3G53440 |
| SDG40 | 0.38524995 | 0.020754264 | 0.159293859 | 0.018909150 | 0.006692161 | 0.089329854 | 0.009535127 | 0.059681698 | 0.000000000 | 0.021053840 | 0.000000000 | AT5G17240 | 0.025601311 | 0.180048123 | 0.158546679 | 0.20110196 | 0.021053840 | SDG40 |
| SUVH5 | 0.36632909 | 0.105951087 | 0.028363536 | 0.091486809 | 0.000000000 | 0.000000000 | 0.000000000 | 0.006320216 | 0.037184798 | 0.066305449 | 0.030717196 | AT2G35160 | 0.091486809 | 0.134314623 | 0.043505014 | 0.20062007 | 0.097022645 | SUVH5 |
| TAF6B | 0.34631662 | 0.011770842 | 0.025418396 | 0.000000000 | 0.002868069 | 0.007939713 | 0.000000000 | 0.000000000 | 0.036052968 | 0.137916985 | 0.124349649 | AT1G54360 | 0.002868069 | 0.037189238 | 0.043992680 | 0.17510622 | 0.262266634 | TAF6B |
| RAD5 | 0.29916515 | 0.059735152 | 0.010257687 | 0.010984046 | 0.000000000 | 0.044776504 | 0.003733243 | 0.005016544 | 0.039960460 | 0.093256572 | 0.031444947 | AT5G22750 | 0.010984046 | 0.069992839 | 0.093486750 | 0.16324941 | 0.124701520 | RAD5 |
| AT3G46950 | 0.29391747 | 0.094381189 | 0.051071576 | 0.086813219 | 0.000000000 | 0.012038951 | 0.016494022 | 0.000000000 | 0.000000000 | 0.016081184 | 0.017037331 | AT3G46950 | 0.086813219 | 0.145452765 | 0.028532974 | 0.16153395 | 0.033118514 | AT3G46950 |
| AT2G47090 | 0.29523820 | 0.035613769 | 0.009397183 | 0.008213963 | 0.004780115 | 0.000000000 | 0.022959660 | 0.006287192 | 0.022933347 | 0.107450839 | 0.077602132 | AT2G47090 | 0.012994078 | 0.045010953 | 0.052180199 | 0.15246179 | 0.185052971 | AT2G47090 |
| LSMT-L | 0.23580468 | 0.042956628 | 0.007096180 | 0.016300684 | 0.000000000 | 0.000000000 | 0.000000000 | 0.005611100 | 0.022608874 | 0.096084779 | 0.045146431 | AT1G14030 | 0.016300684 | 0.050052808 | 0.028219974 | 0.14613759 | 0.141231210 | LSMT-L |
| AT2G37000 | 0.17297214 | 0.056940627 | 0.080660118 | 0.031252544 | 0.000000000 | 0.000000000 | 0.004118849 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT2G37000 | 0.031252544 | 0.137600745 | 0.004118849 | 0.13760075 | 0.000000000 | AT2G37000 |
| CHR23 | 0.23323803 | 0.000000000 | 0.017757332 | 0.000000000 | 0.009560229 | 0.000000000 | 0.032041241 | 0.000000000 | 0.038840850 | 0.106255994 | 0.028782379 | AT5G19310 | 0.009560229 | 0.017757332 | 0.070882091 | 0.12401333 | 0.135038373 | CHR23 |
| FRF1 | 0.19864460 | 0.042163366 | 0.080878020 | 0.005836971 | 0.028956831 | 0.000000000 | 0.026028442 | 0.000000000 | 0.014780966 | 0.000000000 | 0.000000000 | AT3G59470 | 0.034793803 | 0.123041386 | 0.040809407 | 0.12304139 | 0.000000000 | FRF1 |
| AT3G24860 | 0.22581823 | 0.000000000 | 0.009373312 | 0.000000000 | 0.008604207 | 0.000000000 | 0.029893829 | 0.000000000 | 0.033688852 | 0.104816204 | 0.039441828 | AT3G24860 | 0.008604207 | 0.009373312 | 0.063582681 | 0.11418952 | 0.144258032 | AT3G24860 |
| NBS1 | 0.15534389 | 0.000000000 | 0.037174125 | 0.021679233 | 0.026348207 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.070142324 | 0.000000000 | AT3G02680 | 0.048027440 | 0.037174125 | 0.000000000 | 0.10731645 | 0.070142324 | NBS1 |
| MYB1 | 0.20603320 | 0.022388060 | 0.032148297 | 0.000000000 | 0.003824092 | 0.000000000 | 0.007847078 | 0.005049568 | 0.011571138 | 0.050851264 | 0.072353708 | AT3G09230 | 0.003824092 | 0.054536357 | 0.024467783 | 0.10538762 | 0.123204973 | MYB1 |
| RRS1 | 0.13666857 | 0.016373195 | 0.040227781 | 0.000000000 | 0.035855849 | 0.002863808 | 0.005302323 | 0.002508272 | 0.008569101 | 0.024968238 | 0.000000000 | AT5G45260 | 0.035855849 | 0.056600976 | 0.019243504 | 0.08156921 | 0.024968238 | RRS1 |
| AT3G20280 | 0.14763405 | 0.000000000 | 0.025533502 | 0.000000000 | 0.007648184 | 0.000000000 | 0.036230811 | 0.000000000 | 0.000000000 | 0.055659944 | 0.022561606 | AT3G20280 | 0.007648184 | 0.025533502 | 0.036230811 | 0.08119345 | 0.078221550 | AT3G20280 |
| AT3G01890 | 0.14322741 | 0.000000000 | 0.068670324 | 0.000000000 | 0.055765367 | 0.000000000 | 0.013431320 | 0.000000000 | 0.000000000 | 0.005360395 | 0.000000000 | AT3G01890 | 0.055765367 | 0.068670324 | 0.013431320 | 0.07403072 | 0.005360395 | AT3G01890 |
| AT3G51180 | 0.09952575 | 0.040510867 | 0.025093365 | 0.000000000 | 0.028619193 | 0.000000000 | 0.005302323 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | AT3G51180 | 0.028619193 | 0.065604232 | 0.005302323 | 0.06560423 | 0.000000000 | AT3G51180 |
| APTX | 0.09391715 | 0.000000000 | 0.032778682 | 0.000000000 | 0.003824092 | 0.000000000 | 0.011203017 | 0.000000000 | 0.000000000 | 0.027759969 | 0.018351391 | AT5G01310 | 0.003824092 | 0.032778682 | 0.011203017 | 0.06053865 | 0.046111361 | APTX |
| AT1G61960 | 0.05563907 | 0.022946386 | 0.020899162 | 0.000000000 | 0.002868069 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.008925457 | 0.000000000 | AT1G61960 | 0.002868069 | 0.043845548 | 0.000000000 | 0.05277100 | 0.008925457 | AT1G61960 |
| LDL2 | 0.03974279 | 0.000000000 | 0.019362854 | 0.000000000 | 0.002868069 | 0.000000000 | 0.013934001 | 0.000000000 | 0.000000000 | 0.003577863 | 0.000000000 | AT3G13682 | 0.002868069 | 0.019362854 | 0.013934001 | 0.02294072 | 0.003577863 | LDL2 |
| AT2G25650 | 0.02857585 | 0.000000000 | 0.003293898 | 0.000000000 | 0.003824092 | 0.000000000 | 0.002726091 | 0.000000000 | 0.000000000 | 0.014273050 | 0.004458715 | AT2G25650 | 0.003824092 | 0.003293898 | 0.002726091 | 0.01756695 | 0.018731765 | AT2G25650 |
options(repr.plot.width=8, repr.plot.height=40)
ggplot(epilrc_rank, aes(x=reorder(GeneName, epilrc, decreasing = FALSE), y=epilrc)) + geom_point(size=4)+
labs(title="Epidermis+LRC-specific TF Prioritization",x="", y = "Combined centrality score (betweeness, out and in degree)")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(epilrc_rank,"Epidermis_LRC_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- epilrc_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Epidermis (includes LRC)", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
stele_rank <- bc_rank[which(bc_rank$stele*2 > bc_rank$all),]%>% arrange(desc(stele))
stele_rank <- stele_rank[-c(match(rownames(per_rank), rownames(stele_rank)),match(rownames(pro_rank), rownames(stele_rank)),match(rownames(xyl_rank), rownames(stele_rank)),match(rownames(phl_rank), rownames(stele_rank))),]
stele_rank$GeneName <- rownames(stele_rank)
stele_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | ground | epi | stele | epilrc | rc | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | |
| BZIP9 | 31.42213 | 0.0000000 | 0.000000000 | 0.000000000 | 0.005736138 | 8.553166 | 11.880881 | 0.02003315 | 10.9623184 | 0.00000000 | 0.00000000 | AT5G24800 | 0.005736138 | 0.000000000 | 31.41640 | 0.000000000 | 0.00000000 | BZIP9 |
| AT3G43430 | 29.05965 | 0.0000000 | 0.000000000 | 0.005443880 | 0.029360833 | 9.206565 | 11.246261 | 1.83863137 | 6.7333880 | 0.00000000 | 0.00000000 | AT3G43430 | 0.034804713 | 0.000000000 | 29.02485 | 0.000000000 | 0.00000000 | AT3G43430 |
| AT1G29160 | 20.93074 | 0.0000000 | 0.007980554 | 0.000000000 | 0.000000000 | 5.300742 | 8.291064 | 0.01739278 | 6.9113765 | 0.29583475 | 0.10635337 | AT1G29160 | 0.000000000 | 0.007980554 | 20.52058 | 0.303815309 | 0.40218812 | AT1G29160 |
| HAT2 | 28.63636 | 0.0000000 | 0.000000000 | 3.383183277 | 5.196087392 | 8.800066 | 5.980222 | 2.15045514 | 2.8538731 | 0.00000000 | 0.27247690 | AT5G47370 | 8.579270669 | 0.000000000 | 19.78462 | 0.000000000 | 0.27247690 | HAT2 |
| LEP | 33.01792 | 3.4900788 | 4.098860845 | 1.342756899 | 4.318706696 | 12.181573 | 5.664612 | 0.18424811 | 1.6862749 | 0.05081244 | 0.00000000 | AT5G13910 | 5.661463595 | 7.588939598 | 19.71671 | 7.639752038 | 0.05081244 | LEP |
| AT1G61660 | 19.23311 | 0.0000000 | 0.000000000 | 0.000000000 | 0.003824092 | 4.814712 | 9.091004 | 1.19149612 | 4.1320698 | 0.00000000 | 0.00000000 | AT1G61660 | 0.003824092 | 0.000000000 | 19.22928 | 0.000000000 | 0.00000000 | AT1G61660 |
| MYB20 | 19.00219 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | 6.531919 | 8.922408 | 1.41822212 | 2.1296419 | 0.00000000 | 0.00000000 | AT1G66230 | 0.000000000 | 0.000000000 | 19.00219 | 0.000000000 | 0.00000000 | MYB20 |
| HB-8 | 16.99321 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.315505 | 6.403682 | 7.77220968 | 1.4829019 | 0.00000000 | 0.01891338 | AT4G32880 | 0.000000000 | 0.000000000 | 16.97430 | 0.000000000 | 0.01891338 | HB-8 |
| AT5G05790 | 17.18280 | 0.0000000 | 0.000000000 | 0.003861004 | 0.224853405 | 6.253012 | 3.438334 | 0.34310536 | 6.9196381 | 0.00000000 | 0.00000000 | AT5G05790 | 0.228714409 | 0.000000000 | 16.95409 | 0.000000000 | 0.00000000 | AT5G05790 |
| AT3G60490 | 16.33787 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | 3.380432 | 6.823784 | 0.12843453 | 6.0052202 | 0.00000000 | 0.00000000 | AT3G60490 | 0.000000000 | 0.000000000 | 16.33787 | 0.000000000 | 0.00000000 | AT3G60490 |
| GBF6 | 17.43899 | 0.0000000 | 0.000000000 | 0.205070456 | 0.841471637 | 3.189423 | 5.650735 | 2.15984172 | 5.3144219 | 0.01718324 | 0.06084192 | AT4G34590 | 1.046542093 | 0.000000000 | 16.31442 | 0.017183238 | 0.07802516 | GBF6 |
| IAA12 | 15.30428 | 0.0000000 | 0.000000000 | 0.000000000 | 0.003074926 | 2.513093 | 6.718497 | 4.91679601 | 1.1528143 | 0.00000000 | 0.00000000 | AT1G04550 | 0.003074926 | 0.000000000 | 15.30120 | 0.000000000 | 0.00000000 | IAA12 |
| AT2G34140 | 22.57599 | 0.1659450 | 0.000000000 | 0.052535293 | 0.000000000 | 5.437538 | 6.869162 | 0.01250833 | 2.8411830 | 4.83478544 | 2.36233103 | AT2G34140 | 0.052535293 | 0.165945010 | 15.16039 | 5.000730448 | 7.19711647 | AT2G34140 |
| DAG1 | 15.07165 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | 3.917813 | 7.064960 | 0.60312805 | 3.4857454 | 0.00000000 | 0.00000000 | AT3G61850 | 0.000000000 | 0.000000000 | 15.07165 | 0.000000000 | 0.00000000 | DAG1 |
| GRP2B | 19.35698 | 0.7128001 | 0.203070632 | 1.308341103 | 0.914635876 | 2.526467 | 2.783084 | 4.90924834 | 4.2656234 | 1.05946927 | 0.67424107 | AT2G21060 | 2.222976979 | 0.915870771 | 14.48442 | 1.975340039 | 1.73371034 | GRP2B |
| BT1 | 14.40768 | 0.0000000 | 0.000000000 | 0.068990233 | 0.203175898 | 2.477186 | 6.323171 | 4.01500880 | 1.3201442 | 0.00000000 | 0.00000000 | AT5G63160 | 0.272166130 | 0.000000000 | 14.13551 | 0.000000000 | 0.00000000 | BT1 |
| HAT1 | 22.90158 | 1.5219280 | 0.214498853 | 1.298988901 | 1.003928797 | 4.247698 | 5.329100 | 1.84570100 | 2.6201942 | 3.23503508 | 1.58450292 | AT4G17460 | 2.302917697 | 1.736426864 | 14.04269 | 4.971461944 | 4.81953800 | HAT1 |
| AT3G11280 | 13.67762 | 0.0000000 | 0.000000000 | 0.000000000 | 0.029399941 | 4.211485 | 4.996863 | 0.00000000 | 4.4398686 | 0.00000000 | 0.00000000 | AT3G11280 | 0.029399941 | 0.000000000 | 13.64822 | 0.000000000 | 0.00000000 | AT3G11280 |
| AT4G30410 | 26.61829 | 2.1394912 | 6.023966126 | 3.087578399 | 1.537332655 | 4.968261 | 5.063052 | 1.55410462 | 1.9766307 | 0.22563299 | 0.04223994 | AT4G30410 | 4.624911054 | 8.163457328 | 13.56205 | 8.389090317 | 0.26787293 | AT4G30410 |
| AT2G41130 | 13.52067 | 0.0886555 | 0.044803544 | 0.180941520 | 0.228545253 | 6.099147 | 3.212655 | 2.88788664 | 0.7780328 | 0.00000000 | 0.00000000 | AT2G41130 | 0.409486773 | 0.133459043 | 12.97772 | 0.133459043 | 0.00000000 | AT2G41130 |
| MIF1 | 14.00925 | 0.0000000 | 0.000000000 | 0.235534657 | 0.849578292 | 4.786948 | 5.053819 | 0.00000000 | 2.9239998 | 0.09949597 | 0.05987183 | AT1G74660 | 1.085112949 | 0.000000000 | 12.76477 | 0.099495970 | 0.15936780 | MIF1 |
| HB40 | 12.57572 | 0.0000000 | 0.009881695 | 0.000000000 | 0.000000000 | 1.695113 | 1.819935 | 3.67421723 | 5.3765778 | 0.00000000 | 0.00000000 | AT4G36740 | 0.000000000 | 0.009881695 | 12.56584 | 0.009881695 | 0.00000000 | HB40 |
| HB-7 | 17.27815 | 0.2763827 | 0.134336075 | 1.869892003 | 2.384461534 | 4.127072 | 6.558106 | 0.10919027 | 1.7292334 | 0.00000000 | 0.08947662 | AT2G46680 | 4.254353537 | 0.410718801 | 12.52360 | 0.410718801 | 0.08947662 | HB-7 |
| BZIP61 | 16.46509 | 1.0773458 | 0.232661098 | 0.831874802 | 1.481109147 | 2.552713 | 4.189810 | 2.02229437 | 3.5338887 | 0.42432748 | 0.11906956 | AT3G58120 | 2.312983949 | 1.310006850 | 12.29871 | 1.734334333 | 0.54339704 | BZIP61 |
| OBP3 | 11.93301 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | 2.605650 | 5.191763 | 0.02514877 | 4.1104477 | 0.00000000 | 0.00000000 | AT3G55370 | 0.000000000 | 0.000000000 | 11.93301 | 0.000000000 | 0.00000000 | OBP3 |
| SGR5 | 11.90470 | 0.0000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.243737 | 4.920273 | 1.76829292 | 3.9724008 | 0.00000000 | 0.00000000 | AT2G01940 | 0.000000000 | 0.000000000 | 11.90470 | 0.000000000 | 0.00000000 | SGR5 |
| AT5G51780 | 14.43478 | 0.2740037 | 0.183873621 | 0.236397042 | 1.958286776 | 4.185277 | 3.107451 | 1.78387660 | 2.7056188 | 0.00000000 | 0.00000000 | AT5G51780 | 2.194683818 | 0.457877276 | 11.78222 | 0.457877276 | 0.00000000 | AT5G51780 |
| AT4G24060 | 12.12088 | 0.0000000 | 0.000000000 | 0.061593613 | 0.295434878 | 2.946540 | 4.410514 | 1.85228368 | 2.5545112 | 0.00000000 | 0.00000000 | AT4G24060 | 0.357028491 | 0.000000000 | 11.76385 | 0.000000000 | 0.00000000 | AT4G24060 |
| ATAUX2-11 | 12.23625 | 0.1096186 | 0.003293898 | 0.129545999 | 0.000000000 | 1.328456 | 3.830691 | 5.73311417 | 0.8226915 | 0.10749513 | 0.17134443 | AT5G43700 | 0.129545999 | 0.112912494 | 11.71495 | 0.220407623 | 0.27883956 | ATAUX2-11 |
| UNE12 | 11.55505 | 0.0000000 | 0.000000000 | 0.000000000 | 0.335338175 | 2.866596 | 5.008999 | 1.70933192 | 1.6347826 | 0.00000000 | 0.00000000 | AT4G02590 | 0.335338175 | 0.000000000 | 11.21971 | 0.000000000 | 0.00000000 | UNE12 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| AT3G07670 | 0.26870441 | 0.000000000 | 0.032851353 | 0.051572430 | 0.000000000 | 0.112085655 | 0.038581244 | 0.000000000 | 0.000000000 | 0.027318995 | 0.006294737 | AT3G07670 | 0.051572430 | 0.032851353 | 0.15066690 | 0.060170349 | 0.033613732 | AT3G07670 |
| bHLH11 | 0.23102660 | 0.022388060 | 0.000000000 | 0.000000000 | 0.000000000 | 0.077664976 | 0.023142061 | 0.000000000 | 0.049136649 | 0.023866683 | 0.034828172 | AT4G36060 | 0.000000000 | 0.022388060 | 0.14994369 | 0.046254743 | 0.058694855 | bHLH11 |
| AT4G21060 | 0.27212465 | 0.000000000 | 0.006079414 | 0.000000000 | 0.004780115 | 0.002982303 | 0.026120529 | 0.007590864 | 0.111557120 | 0.058937981 | 0.054076329 | AT4G21060 | 0.004780115 | 0.006079414 | 0.14825082 | 0.065017395 | 0.113014310 | AT4G21060 |
| TGA6 | 0.22870786 | 0.011770842 | 0.024957756 | 0.000000000 | 0.033268527 | 0.042397237 | 0.040436274 | 0.012508335 | 0.052290618 | 0.000000000 | 0.011078272 | AT3G12250 | 0.033268527 | 0.036728598 | 0.14763246 | 0.036728598 | 0.011078272 | TGA6 |
| PCFS4 | 0.22631735 | 0.000000000 | 0.003293898 | 0.000000000 | 0.051620216 | 0.031140738 | 0.035721705 | 0.008795463 | 0.061766704 | 0.012141185 | 0.021837444 | AT4G04885 | 0.051620216 | 0.003293898 | 0.13742461 | 0.015435083 | 0.033978629 | PCFS4 |
| AT1G10320 | 0.22091154 | 0.004093299 | 0.000000000 | 0.000000000 | 0.007648184 | 0.010767388 | 0.028665008 | 0.000000000 | 0.097396412 | 0.035048599 | 0.037292651 | AT1G10320 | 0.007648184 | 0.004093299 | 0.13682881 | 0.039141898 | 0.072341251 | AT1G10320 |
| FRS11 | 0.17490242 | 0.000000000 | 0.004202144 | 0.000000000 | 0.025413486 | 0.004604770 | 0.040337371 | 0.049539490 | 0.040057134 | 0.000000000 | 0.010748023 | AT1G10240 | 0.025413486 | 0.004202144 | 0.13453876 | 0.004202144 | 0.010748023 | FRS11 |
| AT1G62085 | 0.22777283 | 0.026927104 | 0.049440170 | 0.005443880 | 0.010130063 | 0.049121945 | 0.061755748 | 0.016320279 | 0.006095925 | 0.000000000 | 0.002537712 | AT1G62085 | 0.015573943 | 0.076367274 | 0.13329390 | 0.076367274 | 0.002537712 | AT1G62085 |
| YY1 | 0.26203624 | 0.000000000 | 0.011654047 | 0.000000000 | 0.078151187 | 0.014954204 | 0.069636866 | 0.008795463 | 0.038622775 | 0.011728917 | 0.028492782 | AT4G06634 | 0.078151187 | 0.011654047 | 0.13200931 | 0.023382964 | 0.040221700 | YY1 |
| MDA1 | 0.16234196 | 0.033099943 | 0.000000000 | 0.000000000 | 0.002868069 | 0.036951252 | 0.027019085 | 0.007524815 | 0.054878795 | 0.000000000 | 0.000000000 | AT4G14605 | 0.002868069 | 0.033099943 | 0.12637395 | 0.033099943 | 0.000000000 | MDA1 |
| FRS3 | 0.21621803 | 0.000000000 | 0.007286694 | 0.000000000 | 0.039728519 | 0.008953307 | 0.003185921 | 0.025148766 | 0.087823111 | 0.008938258 | 0.035153454 | AT2G27110 | 0.039728519 | 0.007286694 | 0.12511111 | 0.016224952 | 0.044091712 | FRS3 |
| FRS9 | 0.19554034 | 0.000000000 | 0.000000000 | 0.008213963 | 0.000000000 | 0.036374068 | 0.015381290 | 0.000000000 | 0.068184173 | 0.067386851 | 0.000000000 | AT4G38170 | 0.008213963 | 0.000000000 | 0.11993953 | 0.067386851 | 0.067386851 | FRS9 |
| FRS12 | 0.19669530 | 0.000000000 | 0.000000000 | 0.000000000 | 0.063756702 | 0.032013760 | 0.051767129 | 0.008762439 | 0.023921025 | 0.000000000 | 0.016474242 | AT5G18960 | 0.063756702 | 0.000000000 | 0.11646435 | 0.000000000 | 0.016474242 | FRS12 |
| AT1G62120 | 0.22005516 | 0.000000000 | 0.000000000 | 0.030182055 | 0.000000000 | 0.091132244 | 0.002127720 | 0.020097939 | 0.000000000 | 0.049223651 | 0.027291548 | AT1G62120 | 0.030182055 | 0.000000000 | 0.11335790 | 0.049223651 | 0.076515198 | AT1G62120 |
| AT1G10610 | 0.15608756 | 0.000000000 | 0.000000000 | 0.000000000 | 0.002868069 | 0.004384828 | 0.061691231 | 0.022541422 | 0.020519242 | 0.006339367 | 0.037743406 | AT1G10610 | 0.002868069 | 0.000000000 | 0.10913672 | 0.006339367 | 0.044082773 | AT1G10610 |
| FRS4 | 0.15339031 | 0.000000000 | 0.000000000 | 0.000000000 | 0.041354002 | 0.003151281 | 0.036418750 | 0.008795463 | 0.057298375 | 0.000000000 | 0.006372440 | AT1G76320 | 0.041354002 | 0.000000000 | 0.10566387 | 0.000000000 | 0.006372440 | FRS4 |
| AT2G04740 | 0.18017198 | 0.016326397 | 0.035531181 | 0.000000000 | 0.011679133 | 0.018244257 | 0.022679635 | 0.007524815 | 0.052813362 | 0.015373197 | 0.000000000 | AT2G04740 | 0.011679133 | 0.051857578 | 0.10126207 | 0.067230775 | 0.015373197 | AT2G04740 |
| AT1G61980 | 0.17789455 | 0.000000000 | 0.033830196 | 0.021775520 | 0.026058565 | 0.044767887 | 0.027268172 | 0.000000000 | 0.024194212 | 0.000000000 | 0.000000000 | AT1G61980 | 0.047834085 | 0.033830196 | 0.09623027 | 0.033830196 | 0.000000000 | AT1G61980 |
| SMZ | 0.18637801 | 0.000000000 | 0.014641295 | 0.000000000 | 0.003824092 | 0.000000000 | 0.018802007 | 0.000000000 | 0.075746497 | 0.012678080 | 0.060686040 | AT3G54990 | 0.003824092 | 0.014641295 | 0.09454850 | 0.027319375 | 0.073364120 | SMZ |
| TCP9 | 0.15460231 | 0.000000000 | 0.000000000 | 0.000000000 | 0.061548471 | 0.000000000 | 0.003733243 | 0.063558457 | 0.025762137 | 0.000000000 | 0.000000000 | AT2G45680 | 0.061548471 | 0.000000000 | 0.09305384 | 0.000000000 | 0.000000000 | TCP9 |
| AT4G12850 | 0.13478250 | 0.000000000 | 0.041451839 | 0.000000000 | 0.002868069 | 0.004384828 | 0.000000000 | 0.058849233 | 0.027228533 | 0.000000000 | 0.000000000 | AT4G12850 | 0.002868069 | 0.041451839 | 0.09046259 | 0.041451839 | 0.000000000 | AT4G12850 |
| NAC027 | 0.15560843 | 0.000000000 | 0.060812596 | 0.000000000 | 0.003824092 | 0.053104103 | 0.002127720 | 0.000000000 | 0.022616614 | 0.000000000 | 0.013123306 | AT1G64105 | 0.003824092 | 0.060812596 | 0.07784844 | 0.060812596 | 0.013123306 | NAC027 |
| TRFL5 | 0.13184321 | 0.000000000 | 0.003293898 | 0.000000000 | 0.002868069 | 0.044776504 | 0.014323089 | 0.000000000 | 0.016836004 | 0.049745645 | 0.000000000 | AT1G15720 | 0.002868069 | 0.003293898 | 0.07593560 | 0.053039544 | 0.049745645 | TRFL5 |
| U2AF35B | 0.12356777 | 0.000000000 | 0.000000000 | 0.000000000 | 0.004780115 | 0.000000000 | 0.017979996 | 0.016881811 | 0.032582460 | 0.040008173 | 0.011335219 | AT5G42820 | 0.004780115 | 0.000000000 | 0.06744427 | 0.040008173 | 0.051343393 | U2AF35B |
| TAF12 | 0.11331979 | 0.000000000 | 0.004686656 | 0.000000000 | 0.011472275 | 0.041935595 | 0.017108604 | 0.000000000 | 0.007108071 | 0.018946504 | 0.012062083 | AT3G10070 | 0.011472275 | 0.004686656 | 0.06615227 | 0.023633160 | 0.031008587 | TAF12 |
| TTR1 | 0.11847016 | 0.000000000 | 0.003293898 | 0.000000000 | 0.002868069 | 0.022680373 | 0.000000000 | 0.000000000 | 0.039403136 | 0.024848451 | 0.025376229 | AT5G45050 | 0.002868069 | 0.003293898 | 0.06208351 | 0.028142349 | 0.050224680 | TTR1 |
| EMB93 | 0.07726139 | 0.000000000 | 0.003293898 | 0.000000000 | 0.007648184 | 0.000000000 | 0.016987805 | 0.020403999 | 0.022896464 | 0.000000000 | 0.006031042 | AT2G03050 | 0.007648184 | 0.003293898 | 0.06028827 | 0.003293898 | 0.006031042 | EMB93 |
| NF-YB3 | 0.05277951 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.012766319 | 0.014790823 | 0.025222370 | 0.000000000 | 0.000000000 | AT4G14540 | 0.000000000 | 0.000000000 | 0.05277951 | 0.000000000 | 0.000000000 | NF-YB3 |
| AT5G06420 | 0.06037783 | 0.000000000 | 0.011520326 | 0.005836971 | 0.009560229 | 0.000000000 | 0.011203017 | 0.000000000 | 0.022257289 | 0.000000000 | 0.000000000 | AT5G06420 | 0.015397201 | 0.011520326 | 0.03346031 | 0.011520326 | 0.000000000 | AT5G06420 |
| MYB64 | 0.04324678 | 0.000000000 | 0.005195039 | 0.005443880 | 0.000000000 | 0.000000000 | 0.000000000 | 0.020403999 | 0.012203865 | 0.000000000 | 0.000000000 | AT5G11050 | 0.005443880 | 0.005195039 | 0.03260786 | 0.005195039 | 0.000000000 | MYB64 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(stele_rank[1:10,], aes(x=reorder(GeneName, stele, decreasing = FALSE), y=stele)) + geom_point(size=4)+
labs(title="Stele-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(stele_rank,"Stele_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- stele_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Stele", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))
rc_rank <- bc_rank[which(bc_rank$rc*2 > bc_rank$all),]%>% arrange(desc(rc))
rc_rank <- rc_rank[-c(match(rownames(lrc_rank), rownames(rc_rank)),match(rownames(col_rank), rownames(rc_rank))),]
rc_rank$GeneName <- rownames(rc_rank)
rc_rank
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | ground | epi | stele | epilrc | rc | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | |
| NAI1 | 26.293062 | 4.5314653 | 2.427442200 | 0.44536331 | 0.205157772 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 10.314757 | 8.368876 | AT2G22770 | 0.650521086 | 6.9589075 | 0.000000000 | 17.273665 | 18.683633 | NAI1 |
| BT2 | 21.465456 | 3.1938182 | 1.318831580 | 0.18657044 | 0.008604207 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 8.804608 | 7.953024 | AT3G48360 | 0.195174642 | 4.5126498 | 0.000000000 | 13.317258 | 16.757632 | BT2 |
| PLT1 | 23.975143 | 3.9406082 | 0.000000000 | 2.00953127 | 1.492057686 | 0.056998421 | 0.000000000 | 0.000000000 | 0.000000000 | 9.148008 | 7.327940 | AT3G20840 | 3.501588961 | 3.9406082 | 0.056998421 | 13.088616 | 16.475948 | PLT1 |
| AT1G32700 | 20.287087 | 0.1296096 | 0.000000000 | 0.04078096 | 0.127253345 | 0.687116252 | 1.191763395 | 0.276300728 | 2.201376646 | 6.967438 | 8.665448 | AT1G32700 | 0.168034301 | 0.1296096 | 4.356557021 | 7.097048 | 15.632886 | AT1G32700 |
| AT1G36060 | 19.317669 | 3.2888697 | 0.911066727 | 0.41545573 | 0.417050853 | 0.014384784 | 0.000000000 | 0.000000000 | 0.000000000 | 7.431263 | 6.839578 | AT1G36060 | 0.832506586 | 4.1999364 | 0.014384784 | 11.631200 | 14.270841 | AT1G36060 |
| AT1G26680 | 17.564236 | 2.1107861 | 0.000000000 | 1.49577760 | 0.073110164 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 8.564404 | 5.320157 | AT1G26680 | 1.568887761 | 2.1107861 | 0.000000000 | 10.675190 | 13.884562 | AT1G26680 |
| LBD15 | 19.199671 | 1.9941258 | 0.583368907 | 0.18501785 | 0.012611943 | 0.000000000 | 0.000000000 | 2.574826946 | 0.000000000 | 7.823366 | 6.026353 | AT2G40470 | 0.197629793 | 2.5774947 | 2.574826946 | 10.400861 | 13.849719 | LBD15 |
| CRF3 | 23.156426 | 3.7281317 | 2.509432523 | 1.56346321 | 1.455509716 | 0.227972445 | 0.046967234 | 0.000000000 | 0.007808814 | 9.414626 | 4.202514 | AT5G53290 | 3.018972922 | 6.2375642 | 0.282748493 | 15.652190 | 13.617140 | CRF3 |
| SMB | 18.647620 | 3.7951559 | 0.154934264 | 1.38856149 | 0.208595675 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 6.953647 | 6.146726 | AT1G79580 | 1.597157170 | 3.9500901 | 0.000000000 | 10.903737 | 13.100372 | SMB |
| BRON | 21.210029 | 4.1134431 | 1.541404242 | 1.77862470 | 0.797459038 | 0.029490525 | 0.000000000 | 0.000000000 | 0.000000000 | 8.377749 | 4.571859 | AT1G75710 | 2.576083735 | 5.6548473 | 0.029490525 | 14.032596 | 12.949608 | BRON |
| AXR3 | 18.658641 | 3.6588187 | 0.025869489 | 0.64545698 | 0.017001939 | 0.994908448 | 2.219597404 | 0.011270711 | 0.111210919 | 3.821295 | 7.153212 | AT1G04250 | 0.662458915 | 3.6846882 | 3.336987482 | 7.505983 | 10.974507 | AXR3 |
| NAC094 | 17.625583 | 4.0475056 | 0.006587797 | 1.71460543 | 1.039673292 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 6.450496 | 4.366715 | AT5G39820 | 2.754278725 | 4.0540934 | 0.000000000 | 10.504590 | 10.817211 | NAC094 |
| AGL21 | 14.891367 | 1.5372448 | 0.000000000 | 1.92037615 | 0.138174292 | 0.220039235 | 0.260515696 | 0.017557903 | 0.091092158 | 6.146731 | 4.559636 | AT4G37940 | 2.058550446 | 1.5372448 | 0.589204992 | 7.683976 | 10.706367 | AGL21 |
| AIL6 | 12.164641 | 1.1830156 | 0.043217853 | 0.72578745 | 0.191486449 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 4.812291 | 5.208843 | AT5G10510 | 0.917273900 | 1.2262334 | 0.000000000 | 6.038525 | 10.021134 | AIL6 |
| SPT | 13.734230 | 1.9285344 | 0.000000000 | 0.87954458 | 0.315754768 | 0.229104048 | 0.168832278 | 0.219305866 | 0.067813143 | 5.218644 | 4.706697 | AT4G36930 | 1.195299352 | 1.9285344 | 0.685055335 | 7.147178 | 9.925341 | SPT |
| BIM1 | 13.429095 | 1.8938991 | 0.183470746 | 0.44619358 | 0.174845577 | 0.367434232 | 0.395296609 | 0.021336822 | 0.388532254 | 5.276753 | 4.281332 | AT5G08130 | 0.621039159 | 2.0773698 | 1.172599917 | 7.354123 | 9.558086 | BIM1 |
| FEZ | 15.332752 | 3.3755338 | 0.000000000 | 1.81489600 | 0.697963324 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 5.649530 | 3.794829 | AT1G26870 | 2.512859324 | 3.3755338 | 0.000000000 | 9.025063 | 9.444359 | FEZ |
| RAV2 | 12.419247 | 0.2414081 | 0.008488937 | 0.00000000 | 0.004780115 | 0.591232196 | 1.826101451 | 0.143994572 | 0.318591046 | 4.397419 | 4.887231 | AT1G68840 | 0.004780115 | 0.2498970 | 2.879919265 | 4.647316 | 9.284650 | RAV2 |
| WRKY15 | 11.467317 | 0.6642345 | 0.000000000 | 0.98076472 | 0.425257859 | 0.000000000 | 0.070440566 | 0.059492301 | 0.032870208 | 4.046072 | 5.188185 | AT2G23320 | 1.406022582 | 0.6642345 | 0.162803075 | 4.710306 | 9.234257 | WRKY15 |
| WRKY9 | 16.059040 | 3.4190586 | 3.623664192 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 7.332666 | 1.683652 | AT1G68150 | 0.000000000 | 7.0427228 | 0.000000000 | 14.375388 | 9.016318 | WRKY9 |
| ZFP5 | 14.356045 | 2.1352356 | 0.142448740 | 0.00000000 | 0.000000000 | 0.107545623 | 0.331890146 | 2.760292882 | 0.037982619 | 4.874339 | 3.966310 | AT1G10480 | 0.000000000 | 2.2776844 | 3.237711271 | 7.152024 | 8.840649 | ZFP5 |
| ATL6 | 12.251980 | 1.8948191 | 0.045127586 | 1.30469935 | 0.129259777 | 0.026669574 | 0.265760605 | 0.044362394 | 0.133612769 | 4.212961 | 4.194708 | AT3G05200 | 1.433959129 | 1.9399467 | 0.470405341 | 6.152907 | 8.407669 | ATL6 |
| ARF16 | 13.237412 | 2.3364059 | 1.817921968 | 0.57252527 | 0.260294865 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 5.440638 | 2.809626 | AT4G30080 | 0.832820139 | 4.1543278 | 0.000000000 | 9.594966 | 8.250264 | ARF16 |
| AT1G22190 | 12.423250 | 3.1425199 | 0.104379338 | 0.86106966 | 0.121072079 | 0.000000000 | 0.061920525 | 0.094488107 | 0.005574178 | 4.676885 | 3.355342 | AT1G22190 | 0.982141741 | 3.2468992 | 0.161982810 | 7.923784 | 8.032226 | AT1G22190 |
| IAA33 | 12.712855 | 1.9498474 | 0.080904357 | 1.23730199 | 1.444092516 | 0.068542296 | 0.000000000 | 0.000000000 | 0.000000000 | 4.658001 | 3.274165 | AT5G57420 | 2.681394509 | 2.0307517 | 0.068542296 | 6.688753 | 7.932167 | IAA33 |
| AT1G49475 | 10.222529 | 1.2095842 | 0.000000000 | 1.19812324 | 0.125493723 | 0.036266195 | 0.073581493 | 0.000000000 | 0.000000000 | 4.845990 | 2.733490 | AT1G49475 | 1.323616968 | 1.2095842 | 0.109847689 | 6.055575 | 7.579481 | AT1G49475 |
| AT1G76580 | 7.678801 | 0.2289487 | 0.000000000 | 0.03037463 | 0.017415270 | 0.004460176 | 0.005989591 | 0.000000000 | 0.026661484 | 3.535009 | 3.829942 | AT1G76580 | 0.047789898 | 0.2289487 | 0.037111251 | 3.763958 | 7.364951 | AT1G76580 |
| EEL | 10.895888 | 2.0561547 | 0.066651133 | 1.20867049 | 0.375224619 | 0.101637600 | 0.000000000 | 0.000000000 | 0.000000000 | 4.135904 | 2.951645 | AT2G41070 | 1.583895114 | 2.1228058 | 0.101637600 | 6.258710 | 7.087550 | EEL |
| AT4G39780 | 11.998391 | 0.7067230 | 1.427670072 | 0.50702444 | 0.401939589 | 0.036642163 | 0.082186498 | 0.000000000 | 1.804884394 | 3.660836 | 3.370484 | AT4G39780 | 0.908964033 | 2.1343931 | 1.923713055 | 5.795229 | 7.031321 | AT4G39780 |
| IAA1 | 12.462540 | 3.7130855 | 1.531036993 | 0.36839421 | 0.026348207 | 0.000000000 | 0.000000000 | 0.007524815 | 0.000000000 | 5.308539 | 1.507612 | AT4G14560 | 0.394742421 | 5.2441225 | 0.007524815 | 10.552661 | 6.816150 | IAA1 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| AT1G77250 | 0.42446752 | 0.032777583 | 0.073026501 | 0.016693775 | 0.026698833 | 0.002863808 | 0.006800194 | 0.000000000 | 0.027738283 | 0.140674630 | 0.097193912 | AT1G77250 | 0.043392609 | 0.105804084 | 0.037402286 | 0.246478714 | 0.23786854 | AT1G77250 |
| AT3G52100 | 0.44581510 | 0.035426745 | 0.047247105 | 0.034628173 | 0.048239650 | 0.000000000 | 0.027733335 | 0.000000000 | 0.026288314 | 0.127497126 | 0.098754653 | AT3G52100 | 0.082867823 | 0.082673851 | 0.054021649 | 0.210170977 | 0.22625178 | AT3G52100 |
| AT1G72030 | 0.36551917 | 0.073569283 | 0.000000000 | 0.021968092 | 0.000000000 | 0.048370026 | 0.009630455 | 0.000000000 | 0.000000000 | 0.161363129 | 0.050618187 | AT1G72030 | 0.021968092 | 0.073569283 | 0.058000481 | 0.234932412 | 0.21198132 | AT1G72030 |
| HSFA8 | 0.41967666 | 0.060946896 | 0.028177887 | 0.000000000 | 0.017208413 | 0.019038236 | 0.000000000 | 0.000000000 | 0.082472685 | 0.168664215 | 0.043168332 | AT1G67970 | 0.017208413 | 0.089124783 | 0.101510921 | 0.257788998 | 0.21183255 | HSFA8 |
| SPL11 | 0.27167266 | 0.000000000 | 0.000000000 | 0.000000000 | 0.009560229 | 0.000000000 | 0.005511606 | 0.000000000 | 0.046017186 | 0.097808866 | 0.112774773 | AT1G27360 | 0.009560229 | 0.000000000 | 0.051528793 | 0.097808866 | 0.21058364 | SPL11 |
| IBM1 | 0.34821415 | 0.030237425 | 0.006281146 | 0.000000000 | 0.041100356 | 0.019577863 | 0.044373543 | 0.002508272 | 0.009581247 | 0.074123186 | 0.120431115 | AT3G07610 | 0.041100356 | 0.036518572 | 0.076040924 | 0.110641758 | 0.19455430 | IBM1 |
| CPSF30 | 0.37167530 | 0.013690228 | 0.061188049 | 0.029700624 | 0.008604207 | 0.014903240 | 0.024464318 | 0.006287192 | 0.023147418 | 0.106973455 | 0.082716572 | AT1G30460 | 0.038304830 | 0.074878277 | 0.068802168 | 0.181851732 | 0.18969003 | CPSF30 |
| AT1G76510 | 0.36698726 | 0.016110991 | 0.011520326 | 0.019005436 | 0.011679133 | 0.034858782 | 0.044712114 | 0.010033087 | 0.029890144 | 0.099989036 | 0.089188215 | AT1G76510 | 0.030684569 | 0.027631316 | 0.119494127 | 0.127620353 | 0.18917725 | AT1G76510 |
| MBD8 | 0.31934406 | 0.007932070 | 0.005195039 | 0.005443880 | 0.025413486 | 0.000000000 | 0.030838268 | 0.010033087 | 0.047009802 | 0.069407100 | 0.118071326 | AT1G22310 | 0.030857366 | 0.013127109 | 0.087881157 | 0.082534209 | 0.18747843 | MBD8 |
| AT4G29000 | 0.32909144 | 0.009851456 | 0.017757332 | 0.000000000 | 0.047968604 | 0.003151281 | 0.047400730 | 0.000000000 | 0.015607306 | 0.077771890 | 0.109582837 | AT4G29000 | 0.047968604 | 0.027608788 | 0.066159317 | 0.105380678 | 0.18735473 | AT4G29000 |
| AT2G47090 | 0.29523820 | 0.035613769 | 0.009397183 | 0.008213963 | 0.004780115 | 0.000000000 | 0.022959660 | 0.006287192 | 0.022933347 | 0.107450839 | 0.077602132 | AT2G47090 | 0.012994078 | 0.045010953 | 0.052180199 | 0.152461792 | 0.18505297 | AT2G47090 |
| AT1G29560 | 0.30122748 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.121965137 | 0.131152955 | 0.048109393 | AT1G29560 | 0.000000000 | 0.000000000 | 0.121965137 | 0.131152955 | 0.17926235 | AT1G29560 |
| AT1G04390 | 0.26806591 | 0.034132838 | 0.008360148 | 0.005836971 | 0.028956831 | 0.000000000 | 0.018890842 | 0.000000000 | 0.003339541 | 0.089169324 | 0.079379417 | AT1G04390 | 0.034793803 | 0.042492986 | 0.022230382 | 0.131662310 | 0.16854874 | AT1G04390 |
| AT2G24650 | 0.24169215 | 0.007932070 | 0.013777189 | 0.000000000 | 0.007648184 | 0.000000000 | 0.012105839 | 0.000000000 | 0.032113303 | 0.090433005 | 0.077682561 | AT2G24650 | 0.007648184 | 0.021709260 | 0.044219143 | 0.112142265 | 0.16811557 | AT2G24650 |
| AT2G41450 | 0.31729877 | 0.016110991 | 0.000000000 | 0.030182055 | 0.042831723 | 0.055599423 | 0.003733243 | 0.000000000 | 0.002047342 | 0.103741821 | 0.063052174 | AT2G41450 | 0.073013779 | 0.016110991 | 0.061380009 | 0.119852812 | 0.16679400 | AT2G41450 |
| AT3G53440 | 0.29755250 | 0.008732049 | 0.067282196 | 0.019005436 | 0.035705883 | 0.000000000 | 0.002127720 | 0.000000000 | 0.000000000 | 0.130320835 | 0.034378383 | AT3G53440 | 0.054711320 | 0.076014245 | 0.002127720 | 0.206335080 | 0.16469922 | AT3G53440 |
| TAFII21 | 0.24289509 | 0.000000000 | 0.007980554 | 0.000000000 | 0.025413486 | 0.003151281 | 0.002127720 | 0.000000000 | 0.050117652 | 0.095735490 | 0.058368906 | AT1G54140 | 0.025413486 | 0.007980554 | 0.055396654 | 0.103716044 | 0.15410440 | TAFII21 |
| HSF1 | 0.26721497 | 0.032673856 | 0.010483291 | 0.000000000 | 0.027663170 | 0.000000000 | 0.009603033 | 0.000000000 | 0.038032842 | 0.088981172 | 0.059777608 | AT4G17750 | 0.027663170 | 0.043157147 | 0.047635876 | 0.132138319 | 0.14875878 | HSF1 |
| AT3G24860 | 0.22581823 | 0.000000000 | 0.009373312 | 0.000000000 | 0.008604207 | 0.000000000 | 0.029893829 | 0.000000000 | 0.033688852 | 0.104816204 | 0.039441828 | AT3G24860 | 0.008604207 | 0.009373312 | 0.063582681 | 0.114189516 | 0.14425803 | AT3G24860 |
| LSMT-L | 0.23580468 | 0.042956628 | 0.007096180 | 0.016300684 | 0.000000000 | 0.000000000 | 0.000000000 | 0.005611100 | 0.022608874 | 0.096084779 | 0.045146431 | AT1G14030 | 0.016300684 | 0.050052808 | 0.028219974 | 0.146137587 | 0.14123121 | LSMT-L |
| HDG11 | 0.19351403 | 0.007932070 | 0.017129213 | 0.000000000 | 0.003824092 | 0.000000000 | 0.017362230 | 0.000000000 | 0.007790552 | 0.046027562 | 0.093448312 | AT1G73360 | 0.003824092 | 0.025061284 | 0.025152782 | 0.071088846 | 0.13947587 | HDG11 |
| CHR23 | 0.23323803 | 0.000000000 | 0.017757332 | 0.000000000 | 0.009560229 | 0.000000000 | 0.032041241 | 0.000000000 | 0.038840850 | 0.106255994 | 0.028782379 | AT5G19310 | 0.009560229 | 0.017757332 | 0.070882091 | 0.124013325 | 0.13503837 | CHR23 |
| MYB1 | 0.20603320 | 0.022388060 | 0.032148297 | 0.000000000 | 0.003824092 | 0.000000000 | 0.007847078 | 0.005049568 | 0.011571138 | 0.050851264 | 0.072353708 | AT3G09230 | 0.003824092 | 0.054536357 | 0.024467783 | 0.105387621 | 0.12320497 | MYB1 |
| AT5G41580 | 0.19697666 | 0.013690228 | 0.020607256 | 0.010984046 | 0.012635156 | 0.000000000 | 0.012206687 | 0.000000000 | 0.027144244 | 0.028538865 | 0.071170183 | AT5G41580 | 0.023619202 | 0.034297484 | 0.039350931 | 0.062836349 | 0.09970905 | AT5G41580 |
| EMF2 | 0.19736921 | 0.009851456 | 0.007286694 | 0.005836971 | 0.024457463 | 0.000000000 | 0.002127720 | 0.007557840 | 0.041497602 | 0.018559839 | 0.080193630 | AT5G51230 | 0.030294435 | 0.017138150 | 0.051183161 | 0.035697989 | 0.09875347 | EMF2 |
| AT3G20280 | 0.14763405 | 0.000000000 | 0.025533502 | 0.000000000 | 0.007648184 | 0.000000000 | 0.036230811 | 0.000000000 | 0.000000000 | 0.055659944 | 0.022561606 | AT3G20280 | 0.007648184 | 0.025533502 | 0.036230811 | 0.081193446 | 0.07822155 | AT3G20280 |
| TCP4 | 0.07782803 | 0.000000000 | 0.000000000 | 0.000000000 | 0.009560229 | 0.000000000 | 0.008476926 | 0.000000000 | 0.000000000 | 0.029050946 | 0.030739923 | AT3G15030 | 0.009560229 | 0.000000000 | 0.008476926 | 0.029050946 | 0.05979087 | TCP4 |
| AT5G07400 | 0.07931352 | 0.000000000 | 0.000000000 | 0.013465270 | 0.004780115 | 0.000000000 | 0.007418725 | 0.000000000 | 0.000000000 | 0.014273050 | 0.039376358 | AT5G07400 | 0.018245385 | 0.000000000 | 0.007418725 | 0.014273050 | 0.05364941 | AT5G07400 |
| AT2G25650 | 0.02857585 | 0.000000000 | 0.003293898 | 0.000000000 | 0.003824092 | 0.000000000 | 0.002726091 | 0.000000000 | 0.000000000 | 0.014273050 | 0.004458715 | AT2G25650 | 0.003824092 | 0.003293898 | 0.002726091 | 0.017566949 | 0.01873177 | AT2G25650 |
| AT4G19650 | 0.02016868 | 0.000000000 | 0.003293898 | 0.000000000 | 0.003824092 | 0.000000000 | 0.002127720 | 0.000000000 | 0.000000000 | 0.003577863 | 0.007345102 | AT4G19650 | 0.003824092 | 0.003293898 | 0.002127720 | 0.006871762 | 0.01092297 | AT4G19650 |
rc_rank[1:50,]
| all | atri | tri | cor | end | per | pro | xyl | phl | lrc | col | GeneID | ground | epi | stele | epilrc | rc | GeneName | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | <dbl> | <dbl> | <dbl> | <dbl> | <dbl> | <chr> | |
| NAI1 | 26.293062 | 4.53146528 | 2.427442200 | 0.44536331 | 0.205157772 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 10.3147574 | 8.368876 | AT2G22770 | 0.650521086 | 6.95890748 | 0.000000000 | 17.273665 | 18.683633 | NAI1 |
| BT2 | 21.465456 | 3.19381823 | 1.318831580 | 0.18657044 | 0.008604207 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 8.8046078 | 7.953024 | AT3G48360 | 0.195174642 | 4.51264981 | 0.000000000 | 13.317258 | 16.757632 | BT2 |
| PLT1 | 23.975143 | 3.94060825 | 0.000000000 | 2.00953127 | 1.492057686 | 0.056998421 | 0.000000000 | 0.000000000 | 0.000000000 | 9.1480076 | 7.327940 | AT3G20840 | 3.501588961 | 3.94060825 | 0.056998421 | 13.088616 | 16.475948 | PLT1 |
| AT1G32700 | 20.287087 | 0.12960958 | 0.000000000 | 0.04078096 | 0.127253345 | 0.687116252 | 1.191763395 | 0.276300728 | 2.201376646 | 6.9674380 | 8.665448 | AT1G32700 | 0.168034301 | 0.12960958 | 4.356557021 | 7.097048 | 15.632886 | AT1G32700 |
| AT1G36060 | 19.317669 | 3.28886970 | 0.911066727 | 0.41545573 | 0.417050853 | 0.014384784 | 0.000000000 | 0.000000000 | 0.000000000 | 7.4312633 | 6.839578 | AT1G36060 | 0.832506586 | 4.19993643 | 0.014384784 | 11.631200 | 14.270841 | AT1G36060 |
| AT1G26680 | 17.564236 | 2.11078613 | 0.000000000 | 1.49577760 | 0.073110164 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 8.5644043 | 5.320157 | AT1G26680 | 1.568887761 | 2.11078613 | 0.000000000 | 10.675190 | 13.884562 | AT1G26680 |
| LBD15 | 19.199671 | 1.99412577 | 0.583368907 | 0.18501785 | 0.012611943 | 0.000000000 | 0.000000000 | 2.574826946 | 0.000000000 | 7.8233664 | 6.026353 | AT2G40470 | 0.197629793 | 2.57749468 | 2.574826946 | 10.400861 | 13.849719 | LBD15 |
| CRF3 | 23.156426 | 3.72813165 | 2.509432523 | 1.56346321 | 1.455509716 | 0.227972445 | 0.046967234 | 0.000000000 | 0.007808814 | 9.4146263 | 4.202514 | AT5G53290 | 3.018972922 | 6.23756418 | 0.282748493 | 15.652190 | 13.617140 | CRF3 |
| SMB | 18.647620 | 3.79515586 | 0.154934264 | 1.38856149 | 0.208595675 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 6.9536467 | 6.146726 | AT1G79580 | 1.597157170 | 3.95009013 | 0.000000000 | 10.903737 | 13.100372 | SMB |
| BRON | 21.210029 | 4.11344307 | 1.541404242 | 1.77862470 | 0.797459038 | 0.029490525 | 0.000000000 | 0.000000000 | 0.000000000 | 8.3777491 | 4.571859 | AT1G75710 | 2.576083735 | 5.65484731 | 0.029490525 | 14.032596 | 12.949608 | BRON |
| AXR3 | 18.658641 | 3.65881868 | 0.025869489 | 0.64545698 | 0.017001939 | 0.994908448 | 2.219597404 | 0.011270711 | 0.111210919 | 3.8212951 | 7.153212 | AT1G04250 | 0.662458915 | 3.68468817 | 3.336987482 | 7.505983 | 10.974507 | AXR3 |
| NAC094 | 17.625583 | 4.04750565 | 0.006587797 | 1.71460543 | 1.039673292 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 6.4504962 | 4.366715 | AT5G39820 | 2.754278725 | 4.05409345 | 0.000000000 | 10.504590 | 10.817211 | NAC094 |
| AGL21 | 14.891367 | 1.53724482 | 0.000000000 | 1.92037615 | 0.138174292 | 0.220039235 | 0.260515696 | 0.017557903 | 0.091092158 | 6.1467312 | 4.559636 | AT4G37940 | 2.058550446 | 1.53724482 | 0.589204992 | 7.683976 | 10.706367 | AGL21 |
| AIL6 | 12.164641 | 1.18301557 | 0.043217853 | 0.72578745 | 0.191486449 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 4.8122911 | 5.208843 | AT5G10510 | 0.917273900 | 1.22623342 | 0.000000000 | 6.038525 | 10.021134 | AIL6 |
| SPT | 13.734230 | 1.92853440 | 0.000000000 | 0.87954458 | 0.315754768 | 0.229104048 | 0.168832278 | 0.219305866 | 0.067813143 | 5.2186441 | 4.706697 | AT4G36930 | 1.195299352 | 1.92853440 | 0.685055335 | 7.147178 | 9.925341 | SPT |
| BIM1 | 13.429095 | 1.89389909 | 0.183470746 | 0.44619358 | 0.174845577 | 0.367434232 | 0.395296609 | 0.021336822 | 0.388532254 | 5.2767535 | 4.281332 | AT5G08130 | 0.621039159 | 2.07736984 | 1.172599917 | 7.354123 | 9.558086 | BIM1 |
| FEZ | 15.332752 | 3.37553381 | 0.000000000 | 1.81489600 | 0.697963324 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 5.6495295 | 3.794829 | AT1G26870 | 2.512859324 | 3.37553381 | 0.000000000 | 9.025063 | 9.444359 | FEZ |
| RAV2 | 12.419247 | 0.24140805 | 0.008488937 | 0.00000000 | 0.004780115 | 0.591232196 | 1.826101451 | 0.143994572 | 0.318591046 | 4.3974193 | 4.887231 | AT1G68840 | 0.004780115 | 0.24989699 | 2.879919265 | 4.647316 | 9.284650 | RAV2 |
| WRKY15 | 11.467317 | 0.66423449 | 0.000000000 | 0.98076472 | 0.425257859 | 0.000000000 | 0.070440566 | 0.059492301 | 0.032870208 | 4.0460720 | 5.188185 | AT2G23320 | 1.406022582 | 0.66423449 | 0.162803075 | 4.710306 | 9.234257 | WRKY15 |
| WRKY9 | 16.059040 | 3.41905862 | 3.623664192 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 7.3326656 | 1.683652 | AT1G68150 | 0.000000000 | 7.04272281 | 0.000000000 | 14.375388 | 9.016318 | WRKY9 |
| ZFP5 | 14.356045 | 2.13523562 | 0.142448740 | 0.00000000 | 0.000000000 | 0.107545623 | 0.331890146 | 2.760292882 | 0.037982619 | 4.8743394 | 3.966310 | AT1G10480 | 0.000000000 | 2.27768435 | 3.237711271 | 7.152024 | 8.840649 | ZFP5 |
| ATL6 | 12.251980 | 1.89481914 | 0.045127586 | 1.30469935 | 0.129259777 | 0.026669574 | 0.265760605 | 0.044362394 | 0.133612769 | 4.2129608 | 4.194708 | AT3G05200 | 1.433959129 | 1.93994673 | 0.470405341 | 6.152907 | 8.407669 | ATL6 |
| ARF16 | 13.237412 | 2.33640587 | 1.817921968 | 0.57252527 | 0.260294865 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 5.4406380 | 2.809626 | AT4G30080 | 0.832820139 | 4.15432784 | 0.000000000 | 9.594966 | 8.250264 | ARF16 |
| AT1G22190 | 12.423250 | 3.14251987 | 0.104379338 | 0.86106966 | 0.121072079 | 0.000000000 | 0.061920525 | 0.094488107 | 0.005574178 | 4.6768845 | 3.355342 | AT1G22190 | 0.982141741 | 3.24689921 | 0.161982810 | 7.923784 | 8.032226 | AT1G22190 |
| IAA33 | 12.712855 | 1.94984738 | 0.080904357 | 1.23730199 | 1.444092516 | 0.068542296 | 0.000000000 | 0.000000000 | 0.000000000 | 4.6580013 | 3.274165 | AT5G57420 | 2.681394509 | 2.03075174 | 0.068542296 | 6.688753 | 7.932167 | IAA33 |
| AT1G49475 | 10.222529 | 1.20958417 | 0.000000000 | 1.19812324 | 0.125493723 | 0.036266195 | 0.073581493 | 0.000000000 | 0.000000000 | 4.8459904 | 2.733490 | AT1G49475 | 1.323616968 | 1.20958417 | 0.109847689 | 6.055575 | 7.579481 | AT1G49475 |
| AT1G76580 | 7.678801 | 0.22894869 | 0.000000000 | 0.03037463 | 0.017415270 | 0.004460176 | 0.005989591 | 0.000000000 | 0.026661484 | 3.5350092 | 3.829942 | AT1G76580 | 0.047789898 | 0.22894869 | 0.037111251 | 3.763958 | 7.364951 | AT1G76580 |
| EEL | 10.895888 | 2.05615467 | 0.066651133 | 1.20867049 | 0.375224619 | 0.101637600 | 0.000000000 | 0.000000000 | 0.000000000 | 4.1359044 | 2.951645 | AT2G41070 | 1.583895114 | 2.12280581 | 0.101637600 | 6.258710 | 7.087550 | EEL |
| AT4G39780 | 11.998391 | 0.70672300 | 1.427670072 | 0.50702444 | 0.401939589 | 0.036642163 | 0.082186498 | 0.000000000 | 1.804884394 | 3.6608363 | 3.370484 | AT4G39780 | 0.908964033 | 2.13439307 | 1.923713055 | 5.795229 | 7.031321 | AT4G39780 |
| IAA1 | 12.462540 | 3.71308551 | 1.531036993 | 0.36839421 | 0.026348207 | 0.000000000 | 0.000000000 | 0.007524815 | 0.000000000 | 5.3085388 | 1.507612 | AT4G14560 | 0.394742421 | 5.24412250 | 0.007524815 | 10.552661 | 6.816150 | IAA1 |
| AT5G03510 | 12.378022 | 0.35100228 | 0.031149052 | 0.00000000 | 0.137191871 | 0.021307799 | 0.020918106 | 4.975736906 | 0.109229651 | 1.5322636 | 5.199223 | AT5G03510 | 0.137191871 | 0.38215133 | 5.127192462 | 1.914415 | 6.731486 | AT5G03510 |
| PLT2 | 12.093601 | 3.21355999 | 0.000000000 | 1.35960481 | 1.006404015 | 0.073726311 | 0.000000000 | 0.000000000 | 0.000000000 | 3.9988320 | 2.441474 | AT1G51190 | 2.366008823 | 3.21355999 | 0.073726311 | 7.212392 | 6.440306 | PLT2 |
| COL5 | 8.235688 | 1.36191425 | 0.164686808 | 0.06105435 | 0.064236712 | 0.069729090 | 0.236178921 | 0.010033087 | 0.007796400 | 2.4645421 | 3.795516 | AT5G57660 | 0.125291066 | 1.52660105 | 0.323737498 | 3.991143 | 6.260058 | COL5 |
| BBX30 | 9.719073 | 0.70769180 | 0.000000000 | 0.93677231 | 0.240096728 | 0.211833771 | 0.514105862 | 0.881010141 | 0.082920728 | 2.7907198 | 3.353922 | AT4G15248 | 1.176869034 | 0.70769180 | 1.689870502 | 3.498412 | 6.144642 | BBX30 |
| ATCTH | 10.114217 | 1.79162690 | 1.005841023 | 0.33627441 | 0.226812548 | 0.153039198 | 0.194615958 | 0.597982220 | 0.105784934 | 4.1070802 | 1.595159 | AT2G25900 | 0.563086961 | 2.79746793 | 1.051422311 | 6.904548 | 5.702239 | ATCTH |
| CHR38 | 7.658272 | 0.83781011 | 0.000000000 | 0.83862016 | 0.054505103 | 0.014690742 | 0.141227245 | 0.000000000 | 0.069894227 | 3.1032199 | 2.598305 | AT3G42670 | 0.893125265 | 0.83781011 | 0.225812214 | 3.941030 | 5.701525 | CHR38 |
| NAC083 | 9.118027 | 0.34584979 | 0.008448429 | 0.86664745 | 1.226519613 | 0.303323618 | 0.646445691 | 0.010066111 | 0.345777910 | 0.8430538 | 4.521895 | AT5G13180 | 2.093167063 | 0.35429822 | 1.305613331 | 1.197352 | 5.364949 | NAC083 |
| AT3G57800 | 6.093701 | 0.15638978 | 0.025466812 | 0.03386951 | 0.000000000 | 0.063042752 | 0.110701942 | 0.005049568 | 0.370642324 | 2.5749567 | 2.753582 | AT3G57800 | 0.033869507 | 0.18185659 | 0.549436586 | 2.756813 | 5.328538 | AT3G57800 |
| CZF1 | 8.084519 | 0.29333471 | 0.016617717 | 0.35008676 | 0.220860228 | 0.586271506 | 0.811711320 | 0.011270711 | 0.702898467 | 3.2191331 | 1.872334 | AT2G40140 | 0.570946983 | 0.30995243 | 2.112152004 | 3.529086 | 5.091468 | CZF1 |
| HSFA7A | 6.438350 | 0.12687303 | 0.007096180 | 0.16904460 | 0.107025362 | 0.173020652 | 0.336185481 | 0.000000000 | 0.587030448 | 2.3208992 | 2.611175 | AT3G51910 | 0.276069961 | 0.13396921 | 1.096236581 | 2.454868 | 4.932074 | HSFA7A |
| AT1G74840 | 7.274395 | 0.39570162 | 0.954840046 | 0.43717474 | 0.336124810 | 0.088868898 | 0.104954759 | 0.518120918 | 0.050515540 | 2.9309542 | 1.457139 | AT1G74840 | 0.773299554 | 1.35054166 | 0.762460115 | 4.281496 | 4.388093 | AT1G74840 |
| AT2G35910 | 4.636897 | 0.23554965 | 0.059364086 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 2.2327001 | 2.109284 | AT2G35910 | 0.000000000 | 0.29491374 | 0.000000000 | 2.527614 | 4.341984 | AT2G35910 |
| RAP2.1 | 5.111611 | 0.00000000 | 0.000000000 | 0.47448042 | 0.011242013 | 0.000000000 | 0.006726091 | 0.771326813 | 0.000000000 | 2.0164139 | 1.831422 | AT1G46768 | 0.485722429 | 0.00000000 | 0.778052904 | 2.016414 | 3.847836 | RAP2.1 |
| AT4G25400 | 5.561647 | 1.01173343 | 0.519961069 | 0.00000000 | 0.095528317 | 0.141937742 | 0.224447786 | 0.000000000 | 0.036259813 | 1.2244679 | 2.307311 | AT4G25400 | 0.095528317 | 1.53169450 | 0.402645341 | 2.756162 | 3.531779 | AT4G25400 |
| ARF6 | 4.612046 | 0.50660587 | 0.033314975 | 0.48257114 | 0.109948770 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.3039451 | 2.175660 | AT1G30330 | 0.592519907 | 0.53992085 | 0.000000000 | 1.843866 | 3.479605 | ARF6 |
| RDUF1 | 4.229145 | 0.44002126 | 0.035950103 | 0.44208233 | 0.069319299 | 0.000000000 | 0.006904364 | 0.000000000 | 0.030089012 | 1.2783165 | 1.926462 | AT3G46620 | 0.511401624 | 0.47597137 | 0.036993376 | 1.754288 | 3.204778 | RDUF1 |
| WRKY14 | 4.012880 | 0.63393072 | 0.225698358 | 0.00000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 0.000000000 | 1.6502378 | 1.503014 | AT1G30650 | 0.000000000 | 0.85962908 | 0.000000000 | 2.509867 | 3.153251 | WRKY14 |
| SCL8 | 4.456934 | 0.09199188 | 0.003992795 | 0.10860697 | 0.050594655 | 0.042578034 | 0.101105099 | 0.795219219 | 0.167179674 | 1.2943751 | 1.801291 | AT5G52510 | 0.159201620 | 0.09598468 | 1.106082026 | 1.390360 | 3.095666 | SCL8 |
| BHLH101 | 3.703793 | 0.23238764 | 0.000000000 | 0.11843957 | 0.009174040 | 0.000000000 | 0.000000000 | 0.000000000 | 0.302435295 | 1.3438272 | 1.697529 | AT5G04150 | 0.127613610 | 0.23238764 | 0.302435295 | 1.576215 | 3.041357 | BHLH101 |
| PIF3 | 3.867586 | 0.27585520 | 0.000000000 | 0.31966574 | 0.041917461 | 0.011872211 | 0.000000000 | 0.000000000 | 0.402717727 | 1.3576067 | 1.457951 | AT1G09530 | 0.361583199 | 0.27585520 | 0.414589938 | 1.633462 | 2.815558 | PIF3 |
options(repr.plot.width=6, repr.plot.height=4)
ggplot(rc_rank[1:10,], aes(x=reorder(GeneName, rc, decreasing = FALSE), y=rc)) + geom_point(size=4)+
labs(title="Root Cap-specific TF Prioritization",x="", y = "Combined centrality score")+
theme_classic()+
theme(axis.text.x = element_text(color = "black",
size = 16, angle = 0),
axis.text.y = element_text( color = "black",
size = 16, angle = 0),
plot.title = element_text(color="black", size=18, face="bold"),
axis.title.x = element_text(color="black", size=16, face="bold"))+ coord_flip()
write.csv(rc_rank,"Root_Cap_TF_centrality_all_transition_zscore3.csv", quote=FALSE, row.names=TRUE)
tf_rank <- rc_rank %>% rownames(.)
# Max 20
p1 <- plot_bc(tf_rank[1]) + plot_bc(tf_rank[2]) + plot_bc(tf_rank[3]) + plot_bc(tf_rank[4]) + plot_bc(tf_rank[5])
p2 <- plot_bc(tf_rank[6]) + plot_bc(tf_rank[7]) + plot_bc(tf_rank[8]) + plot_bc(tf_rank[9]) + plot_bc(tf_rank[10])
p3 <- plot_bc(tf_rank[11]) + plot_bc(tf_rank[12]) + plot_bc(tf_rank[13]) + plot_bc(tf_rank[14]) + plot_bc(tf_rank[15])
p4 <- plot_bc(tf_rank[16]) + plot_bc(tf_rank[17]) + plot_bc(tf_rank[18]) + plot_bc(tf_rank[19]) + plot_bc(tf_rank[20])
p5 <- plot_oc(tf_rank[1]) + plot_oc(tf_rank[2]) + plot_oc(tf_rank[3]) + plot_oc(tf_rank[4]) + plot_oc(tf_rank[5])
p6 <- plot_oc(tf_rank[6]) + plot_oc(tf_rank[7]) + plot_oc(tf_rank[8]) + plot_oc(tf_rank[9]) + plot_oc(tf_rank[10])
p7 <- plot_oc(tf_rank[11]) + plot_oc(tf_rank[12]) + plot_oc(tf_rank[13]) + plot_oc(tf_rank[14]) + plot_oc(tf_rank[15])
p8 <- plot_oc(tf_rank[16]) + plot_oc(tf_rank[17]) + plot_oc(tf_rank[18]) + plot_oc(tf_rank[19]) + plot_oc(tf_rank[20])
p9 <- plot_ic(tf_rank[1]) + plot_ic(tf_rank[2]) + plot_ic(tf_rank[3]) + plot_ic(tf_rank[4]) + plot_ic(tf_rank[5])
p10 <- plot_ic(tf_rank[6]) + plot_ic(tf_rank[7]) + plot_ic(tf_rank[8]) + plot_ic(tf_rank[9]) + plot_ic(tf_rank[10])
p11 <- plot_ic(tf_rank[11]) + plot_ic(tf_rank[12]) + plot_ic(tf_rank[13]) + plot_ic(tf_rank[14]) + plot_ic(tf_rank[15])
p12 <- plot_ic(tf_rank[16]) + plot_ic(tf_rank[17]) + plot_ic(tf_rank[18]) + plot_ic(tf_rank[19]) + plot_ic(tf_rank[20])
p1 <- grid.grabExpr(draw(p1))
p2 <- grid.grabExpr(draw(p2))
p3 <- grid.grabExpr(draw(p3))
p4 <- grid.grabExpr(draw(p4))
p5 <- grid.grabExpr(draw(p5))
p6 <- grid.grabExpr(draw(p6))
p7 <- grid.grabExpr(draw(p7))
p8 <- grid.grabExpr(draw(p8))
p9 <- grid.grabExpr(draw(p9))
p10 <- grid.grabExpr(draw(p10))
p11 <- grid.grabExpr(draw(p11))
p12 <- grid.grabExpr(draw(p12))
col_fun = colorRamp2(c(0, 0.001, 1), c('navy',"khaki1", "red"))
legend_grob1 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "weighted\nnetwork\ncentrality")))
col_fun = colorRamp2(c(0, 0.001, 1), c('gainsboro', "grey", "black"))
legend_grob2 <- grid.grabExpr(draw(Legend(col_fun = col_fun, title = "unweighted\nnetwork\ncentrality")))
options(repr.plot.width=24, repr.plot.height=12)
plot_grid(plot_grid(textbox_grob("Main Regulatory TFs for Root Cap", gp = gpar(fontsize = 20, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),
plot_grid(plot_grid(textbox_grob("Betweenness centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p1,p2,p3,p4,nrow=4),nrow=2,rel_heights = c(1, 14))
,plot_grid(textbox_grob("Out-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p5,p6,p7,p8,nrow=4),nrow=2,rel_heights=c(1,14))
,plot_grid(textbox_grob("In-degree centrality", gp = gpar(fontsize = 16, col='black'), background_gp = gpar(fill = "#FFFFFF", col = NA)),plot_grid(p9,p10,p11,p12,nrow=4),nrow=2,rel_heights=c(1,14)),nrow=1),nrow=2,rel_heights = c(1, 14)),plot_grid(legend_grob1,legend_grob2,nrow=2), rel_widths = c(19, 1))